J. Botzheim

22133853500

Publications - 65

Conceptual Framework for Adaptive Bacterial Memetic Algorithm Parameterization in Storage Location Assignment Problem

J. Botzheim Tamas Bodis Kitti Udvardy Polina Görbe

Publication Name: Mathematics

Publication Date: 2024-12-01

Volume: 12

Issue: 23

Page Range: Unknown

Description:

Recognized as an NP-hard combinatorial challenge, Storage Location Assignment Problem (SLAP) demands heuristic or algorithmic solutions for effective optimization. This paper specifically examines the enhancement of SLAP through the utilization of evolutionary algorithms, as they are particularly suitable for complex cases. Among others, the genetic algorithm (GA) is typically applied to solve this problem. This paper investigates the Bacterial Memetic Algorithm (BMA) as a possible solution for optimization. Though the comparative analysis of the BMA with the previously well-used GA algorithm under certain test parameters reveals that BMA is suitable for SLA optimization, BMA failed to achieve better results. We attribute the unsatisfactory results to the parameter settings, as illustrated by a few specific examples. However, the complexity of the problem and the parameterization does not allow for continuous manual parameter adjustment, which is why we have identified the need for a concept that automatically and adaptively adjusts the parameter settings based on the statistics and fitness values obtained during the execution. The novelty of this paper is to specify the concept of adaptive BMA parameterization and rules.

Open Access: Yes

DOI: 10.3390/math12233688

Human-Centric Automation and Optimization for Smart Homes

J. Botzheim Noel Nuo Wi Tay Naoyuki Kubota

Publication Name: IEEE Transactions on Automation Science and Engineering

Publication Date: 2018-10-01

Volume: 15

Issue: 4

Page Range: 1759-1771

Description:

A smart home needs to be human-centric, where it tries to fulfill human needs given the devices it has. Various works are developed to provide homes with reasoning and planning capability to fulfill goals, but most do not support complex sequence of plans or require significant manual effort in devising subplans. This is further aggravated by the need to optimize conflicting personal goals. A solution is to solve the planning problem represented as constraint satisfaction problem (CSP). But CSP uses hard constraints and, thus, cannot handle optimization and partial goal fulfillment efficiently. This paper aims to extend this approach to weighted CSP. Knowledge representation to help in generating planning rules is also proposed, as well as methods to improve performances. Case studies show that the system can provide intelligent and complex plans from activities generated from semantic annotations of the devices, as well as optimization to maximize personal constraints' fulfillment. Note to Practitioners - Smart home should maximize the fulfillment of personal goals that are often conflicting. For example, it should try to fulfill as much as possible the requests made by both the mother and daughter who wants to watch TV but both having different channel preferences. That said, every person has a set of goals or constraints that they hope the smart home can fulfill. Therefore, human-centric system that automates the loosely coupled devices of the smart home to optimize the goals or constraints of individuals in the home is developed. Automated planning is done using converted services extracted from devices, where conversion is done using existing tools and concepts from Web technologies. Weighted constraint satisfaction that provides the declarative approach to cover large problem domain to realize the automated planner with optimization capability is proposed. Details to speed up planning through search space reduction are also given. Real-time case studies are run in a prototype smart home to demonstrate its applicability and intelligence, where every planning is performed under a maximum of 10 s. The vision of this paper is to be able to implement such system in a community, where devices everywhere can cooperate to ensure the well-being of the community.

Open Access: Yes

DOI: 10.1109/TASE.2018.2789658

Bacterial Memetic Algorithms for Order Picking Routing Problem with Loading Constraints

J. Botzheim Tamas Bodis

Publication Name: Expert Systems with Applications

Publication Date: 2018-09-01

Volume: 105

Issue: Unknown

Page Range: 196-220

Description:

Order picking is the most labour and capital intensive warehousing operation whose primary development field is routing optimisation due to its time consuming nature. The Order Picking Routing Problem is a special case of the vehicle routing problem with loading constraints, when the operator visits picking positions and collects items to build transport unit. Where the stacking and stability challenges are relevant during the picking of ordered items and exact routing algorithms are not available, the order picking operators have huge challenges to sequence the order picking list. They should take into consideration several factors by themselves, such as product properties, order picking list characteristics, and order picking system properties. The goal of the proposed research is to support the order picking operators in order to make more objective decisions in decreasing the order picking lead time, building stable transport units, and avoiding product damages, when industrially relevant, but rarely discussed, order picking sequencing based on stacking property is necessary. The paper defines the Order Picking Routing Problem based on Pallet Loading Feature (OPRP-PLF) and presents Bacterial Memetic Algorithm (BMA) based solutions for it, which is compared to Simulated Annealing (SA) algorithms. BMA has already been applied for Travelling Salesman Problem (TSP) but never used for the defined OPRP-PLF. The paper describes several BMA operators, most of them have an alternative which can be completed with SA based decisions. Using the BMA operators with SA methodology is a novelty of the proposed algorithms, which might support a quicker approximation to the global optimum. The possible combination of BMA operators will be evaluated with shorter and longer order picking lists and compared to SA algorithms on the same basis. The simulation results highlight, that allowing unit load reconstruction could decrease the order picking lead time and the developed BMA algorithms are more effective for OPRP-PLF than the SA algorithms. The paper concludes that the SA combined BMA operators are more effective than the SA-less operators in the case of shorter (less than about 20 records) order picking lists. While the shorter lists are the most commonly occurring order picking lists of warehouses, the SA combined BMA operators can increase the effectiveness of the OPRP-PLF optimisation.

Open Access: Yes

DOI: 10.1016/j.eswa.2018.03.043

Dynamical system algorithm specification analysis and stabilization

J. Botzheim Zhaojie Ju Honghai Liu Cristina Valle Charles C. Phiri Honghai Liu

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2017-01-01

Volume: 10462 LNAI

Issue: Unknown

Page Range: 560-569

Description:

This paper investigates approaches to deliberately designing systems whose controllability can be quantified. Preliminary findings of ongoing research are presented on complex dynamical system control algorithms. The specification analysis and quality of the pressure control algorithm applied to a Topical Negative Pressure Wound Therapy device are conducted, with further discussion on self-regulation mechanism and characterization of both the partially observable and partially controllable workspace represented by the negative pressure chamber. Statistical methods are employed to understand the device physics and fuzzy logic and bacterial memetic algorithm are utilised to explore and optimize the existing algorithms and also extract the rule base.

Open Access: Yes

DOI: 10.1007/978-3-319-65289-4_53

Practical robot edutainment activities program for junior high school students

J. Botzheim Takuya Hashimoto Noriko Takase Naoyuki Takesue Naoyuki Kubota

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2016-01-01

Volume: 9834 LNCS

Issue: Unknown

Page Range: 111-121

Description:

In this paper, we describe the approach of the research activities in order to take advantage of the creativity and thinking abilities in practical research of the robot for junior high school female students. The students mainly understand the main idea and the definition of robots and they created them based on information and advice provided by our university and teachers. As a result, the students created the robots by their unique imagination.

Open Access: Yes

DOI: 10.1007/978-3-319-43506-0_10

Evolving spiking neural network for robot locomotion generation

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: 2015 IEEE Congress on Evolutionary Computation CEC 2015 Proceedings

Publication Date: 2015-09-10

Volume: Unknown

Issue: Unknown

Page Range: 558-565

Description:

In this paper, we propose locomotion generation for a mobile robot. Legged robot can walk in various complex terrains such as stairs as well as in flat environment. However, setting its behaviour to adapt to various environments in advance is very difficult. The robot can mimic the movement of organisms based on computational intelligence. In this study, we apply spiking neural network, which can take into account the transition of temporal information between the neurons. More specifically, the motion patterns are generated by applying a spiking neural network trained by Hebbian learning and evolution strategy, by using data provided by the physics engine measuring the distance walked by the robot and applied the motion patterns to real robot. Simulation was conducted to confirm the proposed technique.

Open Access: Yes

DOI: 10.1109/CEC.2015.7256939

A novel multimodal communication framework using robot partner for aging population

J. Botzheim Dalai Tang Bakhtiar Yusuf Chee Seng Chan Naoyuki Kubota

Publication Name: Expert Systems with Applications

Publication Date: 2015-06-01

Volume: 42

Issue: 9

Page Range: 4540-4555

Description:

In developed country such as Japan, aging has become a serious issue, as there is a disproportionate increasing of elderly population who are no longer able to look after themselves. In order to tackle this issue, we introduce human-friendly robot partner to support the elderly people in their daily life. However, to realize this, it is essential for the robot partner to be able to have a natural communication with the human. This paper proposes a new communication framework between the human and robot partner based on relevance theory as the basis knowledge. The relevance theory is implemented to build mutual cognitive environment between the human and the robot partner, namely as the informationally structured space (ISS). Inside the ISS, robot partner employs both verbal as well as non-verbal communication to understand human. For the verbal communication, Rasmussen's behavior model is implemented as the basis for the conversational system. While for the non-verbal communication, environmental and human state data along with gesture recognition are utilized. These data are used as the perceptual input to compute the robot partner's emotion. Experimental results have shown the effectiveness of our proposed communication framework in establishing natural communication between the human and the robot partner.

Open Access: Yes

DOI: 10.1016/j.eswa.2015.01.016

Spiking neural network based emotional model for robot partner

J. Botzheim Naoyuki Kubota

Publication Name: IEEE Ssci 2014 2014 IEEE Symposium Series on Computational Intelligence Riiss 2014 2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space Proceedings

Publication Date: 2015-01-13

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper, a spiking neural network based emotional model is proposed for a smart phone based robot partner. Since smart phone has limited computational power compared to personal computers, a simple spike response model is applied for the neurons in the neural network. The network has three layers following the concept of emotion, feeling, and mood. The perceptual input stimulates the neurons in the first, emotion layer. Weights adjustment is also proposed for the interconnected neurons in the feeling layer and between the feeling and mood layer based on Hebbian learning. Experiments are presented to validate the proposed method. Based on the emotional model, the output action such as gestural and facial expressions for the robot is calculated.

Open Access: Yes

DOI: 10.1109/RIISS.2014.7009165

Structured learning for extraction of daily life log measured by smart phone sensors

J. Botzheim Naoyuki Kubota

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2015-01-01

Volume: 30

Issue: Unknown

Page Range: 277-293

Description:

This chapter deals with producing information using structured learning to extract daily life log measured by smart phone sensors. Acceleration, angular velocity, and movement distance are measured by smart phone sensors and stored as the entries of the daily life log together with the activity information and timestamp.First, this chapter introduces the concept of Informationally Structured Space (ISS) and explains how smart phones can be used for collecting data for the daily life log. Then, structured learning is proposed for estimating the human activities based on the time series of the measured data. The method applies growing neural gas for performing clustering on the data, and spiking neural network for estimating the activity. A modified simple spike response model is applied to reduce the computational cost. The external input values of the spiking neurons depend on the growing neurons, and various metrics are investigated in the input calculation.Experiments are performed for verifying the effectiveness of the proposed method. Finally, the future direction on this research is discussed.

Open Access: Yes

DOI: 10.1007/978-3-319-13545-8_16

Gestural and facial communication with smart phone based robot partner using emotional model

J. Botzheim Jinseok Woo Noel Tay Nuo Wi Toru Yamaguchi Naoyuki Kubota

Publication Name: World Automation Congress Proceedings

Publication Date: 2014-10-24

Volume: Unknown

Issue: Unknown

Page Range: 644-649

Description:

When conducting natural communication in addition to perform verbal communication, a robot partner should also understand non-verbal communication such as facial and gestural information. The word 'understand' for the robot means how to grasp the meaning of the gesture itself. In this paper we propose a smart phone based system, where an emotional model connects the facial and gestural communication of a human and a robot partner. The input of the emotional model is based on face classification and gesture recognition from the human side. Based on the emotional model, the output action such as gestural and facial expressions for the robot is calculated.

Open Access: Yes

DOI: 10.1109/WAC.2014.6936076

Novel calculation of fuzzy exponent in the sigmoid functions for fuzzy neural networks

J. Botzheim P. Földesi

Publication Name: Neurocomputing

Publication Date: 2014-04-10

Volume: 129

Issue: Unknown

Page Range: 458-466

Description:

This paper presents a novel calculation of fuzzy exponent in the sigmoid functions for fuzzy neural networks. The investigated fuzzy neural network applies fuzzy input signals and crisp connection weights in the network's hidden and output layers. The applied calculation of fuzzy exponent is based on a parametric representation of the fuzzy exponent that is able to provide a crisp output instead of the extension principle's fuzzy output and requires significantly less computational effort than the learning based on α-cuts. For the training of the network the bacterial memetic algorithm is applied which effectively combines the bacterial evolutionary algorithm with gradient based learning. The method is tested on a benchmark problem and on two real datasets. Comparison to the classical technique concerning the learning time is also provided in the paper. © 2013 Elsevier B.V.

Open Access: Yes

DOI: 10.1016/j.neucom.2013.09.013

Interactive training and modeling environment for considering pallet setup features in storage location assignment of order picking zone

J. Botzheim Tamas Bodis Kitti Udvardy

Publication Name: 10th France Japan Congress 8th Europe Asia Congress on Mecatronics Mecatronics 2014

Publication Date: 2014-01-22

Volume: Unknown

Issue: Unknown

Page Range: 64-69

Description:

Order picking is the most labor-intensive and costly activities in many warehouses by consuming ca. 60 % of the total operating expenses. Order picking development strategies mostly concentrate on warehouse layout, storage assignment policy, routing, zoning and on batching methods, while the physical parameters of the products - which are hardly ever taken into account - do also have a significant impact on the processes. Researchers of the pallet-loading problem could provide a wider horizon on considerable parameters, but their results are rarely implemented into order picking processes. In order to design a successful and optimal order picking system, considering all influential parameters is inevitable, since all of them are strongly connected to each other. This paper introduces an interactive training and modeling tool, which allows us to model, test, analyze and to evaluate order picking algorithms by taking numerous influencing factors into consideration. We describe an application of the simulation environment designed for highlighting the importance of physical product parameters in order picking performance.

Open Access: Yes

DOI: 10.1109/MECATRONICS.2014.7018613

Computational intelligence for gestural communication using emotional model

J. Botzheim Bakhtiar Yusuf Toru Yamaguchi Naoyuki Kubota

Publication Name: Iwaciii 2013 3rd International Workshop on Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

When conducting natural communication in addition to perform verbal communication, non-verbal communication such as gestural information should also be understood. By the word "understand" we mean not only the recognition of one action, but also grasp the meaning of the gesture itself. Therefore, in order to understand the meaning of an action, in this paper we propose emotional model along with the gesture recognition technique. First we discuss the gesture recognition method using iPhone camera by applying steady state genetic algorithm, spiking neural network and self organizing map. After that we use the gesture recognition result as an input data for the emotional model.

Open Access: Yes

DOI: DOI not available

Multi-objective optimization of building envelopes by bacterial memetic algorithms

J. Botzheim Árpád Csík

Publication Name: 2013 World Congress on Nature and Biologically Inspired Computing Nabic 2013

Publication Date: 2013-11-22

Volume: Unknown

Issue: Unknown

Page Range: 245-252

Description:

In the present paper, we apply bacterial memetic algorithms in the context of multi-objective optimization. The goal of the development is to optimize the energetic quality of residential building envelopes in a sustainable manner. Our interest is to determine a good compromise between the quality of the building envelope and the total cost of the installed energy saving components. We provide a description of the applied bacterial operators and the particular ordering of the population that is a non unique procedure. In order to refine the ordering we implement a variant of the distance metric for comparing the non-comparable individuals. The numerical computations are performed by the EnergOpt computational framework of the authors. The performance of the algorithm is demonstrated on the solution of a benchmark test case. Finally, the optimization of an existing building is presented to demonstrate the potential of the methodology. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/NaBIC.2013.6617870

Cyclic motion generation for intelligent robot by evolutionary computation

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: Proceedings of the 2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space Riiss 2013 2013 IEEE Symposium Series on Computational Intelligence Ssci 2013

Publication Date: 2013-10-31

Volume: Unknown

Issue: Unknown

Page Range: 13-19

Description:

In this paper we propose a method for motion generation of intelligent multi-legged robot using evolutionary computation. Legged robot can walk in various complex terrains such as stairs as well as in flat environment. However, setting the robot's behavior to adapt to various environments in advance is very difficult. The robot can mimic the movement of organisms based on computational intelligence. In this study we apply steady state genetic algorithm for generating the motion sequence of a six-legged robot modeled by forward kinematics. The number of intermediate positions of the motion sequence is adapted to the environment and optimized as well. We use a computer simulation environment before we apply our method in real robot. This can reduce the time spent on finding the optimal parameter settings and the solution itself for the optimization problem. The solution is evaluated mainly on the moving distance of the robot. Experiments were conducted to confirm the proposed technique. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/RiiSS.2013.6607923

Single-stroke character recognition with fuzzy method

J. Botzheim Alex Tormási

Publication Name: Studies in Computational Intelligence

Publication Date: 2013-01-01

Volume: 417

Issue: Unknown

Page Range: 27-46

Description:

In this paper an on-line single-stroke recognition method based on fuzzy logic is introduced. Each of the characters is defined by only one nine dimensional fuzzy rule. In addition to the low resource requirement the solution is able to satisfy many of the user's current demands in handwriting recognizers, like speed and learning. Eight of the nine features are extracted using a four-by-four grid. For the learning phase we designed a new punish/reward bacterial evolutionary algorithm which tunes the character parameters represented by fuzzy sets. © 2013 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-28959-0_2

Robot edutainment on walking motion of multi-legged robot

J. Botzheim Noriko Takase Naoyuki Kubota

Publication Name: Proceedings 2013 2nd International Conference on Robot Vision and Signal Processing Rvsp 2013

Publication Date: 2013-01-01

Volume: Unknown

Issue: Unknown

Page Range: 229-233

Description:

In this paper we present a short-term robot edutainment for junior high school students. The theme of this robotic course is the walking motion of multi-legged robot. We provided the students with the robot educational material that contains assembled leg parts. The students devised the configuration and motion of the robot using given constraints. We conducted a robot contest for the students to present their results in this robot course. As a result, by using limited materials, the students were able to produce a robot that shows their ingenuity. We could observe from a questionnaire about the course that the students were interested in science and robots. © 2013 IEEE.

Open Access: Yes

DOI: 10.1109/RVSP.2013.59

Extraction of daily life log measured by smart phone sensors using neural computing

J. Botzheim Dalai Tang Takenori Obo Bakhtiar Yusuf Toru Yamaguchi Naoyuki Kubota

Publication Name: Procedia Computer Science

Publication Date: 2013-01-01

Volume: 22

Issue: Unknown

Page Range: 883-892

Description:

This paper deals with the information extraction of daily life log measured by smart phone sensors. Two types of neural computing are applied for estimating the human activities based on the time series of the measured data. Acceleration, angular velocity, and movement distance are measured by the smart phone sensors and stored as the entries of the daily life log together with the activity information and timestamp. First, growing neural gas performs clustering on the data. Then, spiking neural network is applied to estimate the activity. Experiments are performed for verifying the effectiveness of the proposed method. © 2013 The Authors.

Open Access: Yes

DOI: 10.1016/j.procs.2013.09.171

Simultaneous optimization of customer satisfaction and cost function by nature inspired computing

J. Botzheim P. Földesi

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2012-12-01

Volume: 15

Issue: Unknown

Page Range: 309-318

Description:

When optimizing multi-dimensional non-linear problems the optimal solution in technical terms can be found by heuristic methods. It seems that human thinking does not work properlywith the mathematical processing: human decisionmakers tend to reject options that represent extreme values in the set of parameters and are not able to handle many system parameters at the same time. The paper investigates the best possible way for modeling the human thinking, comparing bacterial memetic algorithm and particle swarm optimization in fuzzy environment. © Springer-Verlag Berlin Heidelberg 2012.

Open Access: Yes

DOI: 10.1007/978-3-642-29977-3_31

Improving the Strategic Level Performance Measurement in Warehousing Processes

J. Botzheim P. Földesi Péter Németh

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2012-12-01

Volume: 16

Issue: Unknown

Page Range: 365-374

Description:

In our paper we propose a new method for the strategic level performance measurement at a warehouse in Hungary. The growing challenge of remaining successful in the warehousing forced the given warehouse to introduce and use a new tool for monitoring and forecasting strategic level indicators. Our proposed tool uses computational intelligence to establish connection between basic operational level data and important strategic level indicators. In this article we present the idea behind this tool and the process of programming and learning with company data. Finally, an evaluation is presented based on the results of the program run. © Springer-Verlag Berlin Heidelberg 2012.

Open Access: Yes

DOI: 10.1007/978-3-642-29920-9_37

Human gesture recognition for robot partners by spiking neural network and classification learning

J. Botzheim Takenori Obo Naoyuki Kubota

Publication Name: 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligence Systems Scis Isis 2012

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1954-1958

Description:

Recently, the rate of elderly people rises in the super-aging society. Human-friendly robots can be used to support the mental and physical care for elderly people and to assist the care of caregivers to elderly people. Robotic conversation can activate the brain of such elderly people and improve their concentration and memory abilities. However, it is difficult for a robot to converse appropriately with a person even if many contents of the conversation are designed in advance because the performance of voice recognition is not enough in the daily conversation. Recognition of human gestures is also important in order to perform smooth communication. This paper deals with human gestures recognition using spiking neural network and classification learning. The proposed method is able to handle the cultural differences in the human communication. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/SCIS-ISIS.2012.6505305

Computational method for corrective mechanism of cognitive decision-making biases

J. Botzheim P. Földesi

Publication Name: 3rd IEEE International Conference on Cognitive Infocommunications Coginfocom 2012 Proceedings

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 211-215

Description:

When decisions are made by human beings these choices are often 'predictably irrational'. A large number of different biases effect the human beings' information processing systems. Because of the imperfect information processing system the decisions are imperfect as well, and very often some distortion appears in the solution. In our paper we propose a simple corrective mechanism for the loss aversion bias, presenting Kano's quality model as a case study. An 'interface' is placed between the input data and the optimizing algorithm and the input data are debiased instead of modifying the algorithm itself. The use of fuzzy numbers is adequate to model the loss aversion type bias and corrective tools. Computational results are presented as well to demonstrate the efficiency. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/CogInfoCom.2012.6421982

Path planning in probabilistic environment by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2012-12-01

Volume: 14

Issue: Unknown

Page Range: 439-448

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. In case of probabilistic environment not only static obstacles obstruct the free passage of the robot, but there are appearances of obstacles with probability. The problem is approached by the bacterial memetic algorithm. The objective is to minimize the path length and the number of turns without colliding with an obstacle. Our method is able to generate a collision-free path in probabilistic environment. The proposed algorithm is tested by simulations. © Springer-Verlag Berlin Heidelberg 2012.

Open Access: Yes

DOI: 10.1007/978-3-642-29934-6_42

A novel diversity induction method for bacterial memetic algorithm by hibernation of individuals

J. Botzheim

Publication Name: Proceedings 2012 6th International Conference on Genetic and Evolutionary Computing Icgec 2012

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 328-331

Description:

Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. In this paper a novel diversity induction method is proposed for bacterial memetic algorithm. Hibernation of some individuals in the population is applied for avoiding premature convergence to local optima. This operation can help in turning back from unpromising region of the search space by previously found solutions represented in hibernated bacteria. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/ICGEC.2012.25

Energy and cost optimal design for the reconstruction of residential building envelopes by bacterial memetic algorithms

J. Botzheim József Levente Hontvári János Balázs Árpád Csík Tamás Csoknyai

Publication Name: 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligence Systems Scis Isis 2012

Publication Date: 2012-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1226-1231

Description:

In this paper we apply bacterial memetic algorithms for the energy and cost optimal renovation of residential buildings. Following economical demands, there are two types of optimizations considered. First, the total cost of the renovation is prescribed and the best energy quality of the building envelope is determined with a total construction cost not exceeding the given limit. Second, the targeted energy quality of the renovated building is prescribed, and the algorithm determines the optimal renovation plan requiring the smallest costs. Only the optimization of the building envelope is performed, the optimization of the heating-ventilation-air-condition system is ignored. The chromosome of the bacteria contains genes taking only integer values and genes taking real values as well. The value of the genes taking only integer numbers are improved by a simple local search algorithm. The value of the genes taking real numbers are improved locally by the Levenberg-Marquardt approach. Results of actual building optimizations reveal the potential of the proposed algorithm. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/SCIS-ISIS.2012.6505181

Optimization of strategic level performance measurement and decision making using artificial neural network

J. Botzheim P. Földesi Csaba Tápler Péter Németh

Publication Name: 2012 IEEE International Technology Management Conference Itmc 2012

Publication Date: 2012-11-01

Volume: Unknown

Issue: Unknown

Page Range: 93-97

Description:

In our paper we propose a new method for the strategic level performance measurement and decision making by presenting two case studies performed in 2011. We proposed a computational intelligence method to establish connection between basic operational level data and important strategic level indicators. In the first case study this indicator is related to performance measurement. In the second case study the indicator is the contribution margin of the given company. After the introduction we present the process of programming and learning with actual company data. Finally an evaluation of the results is presented based on the program runs. © 2012 IEEE.

Open Access: Yes

DOI: 10.1109/ITMC.2012.6306360

Bacterial memetic algorithm for simultaneous optimization of path planning and flow shop scheduling problems

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Artificial Life and Robotics

Publication Date: 2012-10-01

Volume: 17

Issue: 1

Page Range: 107-112

Description:

The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the overall time demand of the whole process. In this paper, we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving this combined problem. The algorithm is verified by experimental simulations and compared to classical techniques.

Open Access: Yes

DOI: 10.1007/s10015-012-0021-9

Parametric approximation of fuzzy exponent for computationally intensive problems

J. Botzheim P. Földesi

Publication Name: International Journal of Innovative Computing Information and Control

Publication Date: 2012-08-01

Volume: 8

Issue: 8

Page Range: 5725-5744

Description:

The paper deals with the investigation of the critical non-linear factors and NP-hard problems of real-life decision-making processes. When using non-linear utility/objective functions to represent the value of various options in the search space or when NP-hard problems arise, often soft computing techniques must be applied for optimization. Many times significant uncertainty must be handled as well, so the use of fuzzy numbers can be an efficient method to cope with ambiguity and lack of information. The fuzzy extensions for heuristic based optimizing algorithms often face the problem of an increased number of calculations required to find the solutions. Appropriate representation of the fuzzy power function for non-linear cases is to be used so that it can keep the required computation time and resources at a reasonable level. © 2012 ICIC International.

Open Access: Yes

DOI: DOI not available

Bacterial memetic algorithm for offline path planning of mobile robots

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Memetic Computing

Publication Date: 2012-03-01

Volume: 4

Issue: 1

Page Range: 73-86

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of combinatorial optimization problems which are approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The objective is to minimize the path length and the number of turns without colliding with an obstacle. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The method is able to generate a collision-free path for the robot even in complicated search spaces. The proposed algorithm is tested in real environment. © 2012 Springer-Verlag.

Open Access: Yes

DOI: 10.1007/s12293-012-0076-0

Interpretation of loss aversion in Kano's quality model

J. Botzheim P. Földesi

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2011-12-01

Volume: 10 SIST

Issue: Unknown

Page Range: 165-174

Description:

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target can be the achievement of the minimum overall cost for a given satisfaction level. Kano's quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a non-linear relationship to satisfaction, rather power-function should be used. For the customers' subjective evaluation these relationships are not deterministic and are uncertain. Also the cost function are uncertain, where the loss aversion of decision makers should be considered as well. This paper proposes a method for fuzzy extension of Kano's model and presents numerical examples. © 2011 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-22194-1_17

Representation of loss aversion and impatience concerning time utility in supply chains

J. Botzheim P. Földesi E. Süle

Publication Name: Smart Innovation Systems and Technologies

Publication Date: 2011-12-01

Volume: 10 SIST

Issue: Unknown

Page Range: 273-282

Description:

The paper deals with the investigation of the critical time factor of supply chain. The literature review gives a background to understand and handle the reasons and consequences of the growing importance of time, and the phenomenon of time inconsistency. By using utility functions to represent the value of various delivery-times for the different participants in the supply chain, including the final customers, it is shown that the behaviour and willingness of payment of time-sensitive and non time-sensitive consumers are different for varying lead times. Longer lead times not only generate less utility but impatience influences the decision makers, that is the time elasticity is not constant but it is function of time. For optimization soft computing techniques (particle swarm optimization in this paper) can be efficiently applied. © 2011 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-22194-1_28

Application of evolutionary algorithms for energy efficient building design

J. Botzheim Attila Talamon János Balázs Mihály Retek Árpád Csík Tamás Csoknyai

Publication Name: Iwaciii 2011 International Workshop on Advanced Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2011-12-01

Volume: Unknown

Issue: Unknown

Page Range: 6

Description:

The topic of energy efficient building design is an attractive philosophy in the era of diminishing fossil energy sources drained by the ever increasing thirst of the Earth's population for energy. In this paper we propose to apply evolutionary algorithms aiding the design of energy efficient buildings. We employ a simple mathematical model involving a large number of parameters. Energy efficiency is defined in terms of these parameters through algebraic evaluations. The quasi-optimal values of the fitness function representing the level of energy efficiency are obtained by Bacterial Evolutionary Algorithms. Results indicate that in the case of a prescribed total construction cost close to 80% improvement can be achieved in terms of energy efficiency. On the other hand, if one targets a prescribed energy efficiency, more than 30% of the total construction costs can be saved by proper optimization.

Open Access: Yes

DOI: DOI not available

Path planning for mobile robots by bacterial memetic algorithm

J. Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: IEEE Ssci 2011 Symposium Series on Computational Intelligence Riiss 2011 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space

Publication Date: 2011-08-12

Volume: Unknown

Issue: Unknown

Page Range: 107-112

Description:

The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. This problem belongs to the group of hard optimization problems which can be approached by modern optimization techniques such as evolutionary algorithms. In this paper the bacterial memetic algorithm is proposed for path planning of a mobile robot. The representation used in the paper fits well to the algorithm. Memetic algorithms combine evolutionary algorithms with local search heuristics in order to speed up the evolutionary process. The bacterial memetic algorithm applies the bacterial operators instead of the genetic algorithm's crossover and mutation operator. One advantage of these operators is that they easily can handle individuals with different length. The proposed algorithm is tested in real environment. © 2011 IEEE.

Open Access: Yes

DOI: 10.1109/RIISS.2011.5945787

Eugenic bacterial memetic algorithm for fuzzy road transport traveling salesman problem

J. Botzheim P. Földesi L. T. Koczy

Publication Name: International Journal of Innovative Computing Information and Control

Publication Date: 2011-05-01

Volume: 7

Issue: 5 B

Page Range: 2775-2798

Description:

The aim of the Traveling Salesman Problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities (nodes) exactly once and returning to the starting point. In solutions presented in the literature costs of travel between nodes are based on Euclidean distances, the problem is symmetric and the costs are constant and crisp values. Practical application in road transportation and supply chains are often uncertain or fuzzy. The risk attitude depends on the features of the given operation. The model presented in this paper handles the fuzzy, time dependent nature of the TSP and also gives a solution for the asymmetric loss aversion by embedding the risk attitude into the fitness function of the eugenic bacterial memetic algorithm. Computational results are presented for different cases. The classical TSP is investigated along with a modified instance where some costs between the cities are described with fuzzy numbers. Two different techniques are proposed to evaluate the uncertainties in the fuzzy cost values. The time dependent version of the fuzzy TSP is also investigated and simulation experiences are presented. © 2011.

Open Access: Yes

DOI: DOI not available

Modeling of loss aversion in solving fuzzy road transport traveling salesman problem using eugenic bacterial memetic algorithm

J. Botzheim P. Földesi

Publication Name: Memetic Computing

Publication Date: 2010-12-01

Volume: 2

Issue: 4

Page Range: 259-271

Description:

The aim of the traveling salesman problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities and returning to the starting point. In solutions presented in the literature costs of travel between nodes (cities) are based on Euclidean distances, the problem is symmetric and the costs are constant and crisp values. Practical application in road transportation and supply chains are often fuzzy. The risk attitude depends on the features of the given operation. The model presented in this paper handles the fuzzy, time dependent nature of the TSP and also gives solution for the asymmetric loss aversion by embedding the risk attitude into the fitness function of the bacterial memetic algorithm. Computational results are presented as well. © 2010 Springer-Verlag.

Open Access: Yes

DOI: 10.1007/s12293-010-0037-4

Hierarchical fuzzy system construction applying genetic and bacterial programming algorithms with expression tree building restrictions

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 World Automation Congress Wac 2010

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper various restrictions are proposed in the construction of hierarchical fuzzy rule bases by using Genetic and Bacterial Programming algorithms in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The properties (learning speed, accuracy) of the established systems are observed based on simulation results and they are compared to each other. © 2010 TSI Press.

Open Access: Yes

DOI: DOI not available

Determining an optimal subdivision of gene transfer partitions

J. Botzheim P. Földesi Mark Farkas L. T. Koczy

Publication Name: Proceedings of the 9th Wseas International Conference on Applied Computer and Applied Computational Science Acacos 10

Publication Date: 2010-12-01

Volume: Unknown

Issue: Unknown

Page Range: 202-207

Description:

Bacterial memetic algorithms are widely used on discrete combinatorial problems, which are essential in the field of logistics and forwarding, such as the well known Traveling Salesman Problem. The original Bacterial Evolutionary Algorithm proposed by Nawa and Furuhashi [5] has a predefined set of operators such as bacterial mutation and gene transfer also known as infection. The traditional bacterial infection operator is proven to be far from optimal. The authors suggest an alternative gene transfer operator that is applied on the metric Traveling Salesman Problem [9]. This alternative infection algorithm has superior rate of convergence while reducing the risk of getting stuck in a local optima.

Open Access: Yes

DOI: DOI not available

Hierarchical fuzzy system modeling by genetic and bacterial programming approaches

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper a method is proposed for constructing hierarchical fuzzy rule bases in order to model black box systems defined by input-output pairs, i.e. to solve supervised machine learning problems. The resultant hierarchical rule base is the knowledge base, which is constructed by using structure constructing evolutionary techniques, namely, Genetic and Bacterial Programming Algorithms. Applying hierarchical fuzzy rule bases is a way of reducing the complexity of the knowledge base, whereas evolutionary methods ensure a relatively efficient learning process. This is the reason of the investigation of this combination. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584220

Comparative analysis of interpolative and non-interpolative fuzzy rule based machine learning systems applying various numerical optimization methods

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 2010 IEEE World Congress on Computational Intelligence Wcci 2010

Publication Date: 2010-11-25

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this paper interpolative and non-interpolative fuzzy rule based machine learning systems are investigated by using simulation results. The investigation focuses mainly on two objectives: to compare the efficiency of the inference techniques combined with different numerical optimization methods for solving machine learning problems and to discover the difference between the properties of systems applying interpolative and non-interpolative inference techniques. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2010.5584156

Comparative investigation of various evolutionary and memetic algorithms

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2010-11-03

Volume: 313

Issue: Unknown

Page Range: 129-140

Description:

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared on several numerical optimization benchmark functions and on machine learning problems. © 2010 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-15220-7_11

Fuzzy approach to utility of time factor

J. Botzheim P. Földesi E. Süle

Publication Name: Isciii 09 4th International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2009-12-28

Volume: Unknown

Issue: Unknown

Page Range: 23-29

Description:

The paper deals with the investigation of the critical factor of the supply chain concerning time factor. The literature review can give a background to understand and handle the reasons and consequences of the growing importance of time. By using utility functions to represent the value of various delivery-times for the different participants in the supply chain, including the final customers, it proves through the Kano-model, that the choices, behaviour and willingness of payment of time-sensitive and non time-sensitive consumers are different for varying lead times, so for optimization soft computing techniques must be applied. As the functions are not linear and significant uncertainty must be handled as well, the use of fuzzy numbers is necessary. The features of fuzzy power functions are investigated, and a parametric approaches is presented that can be an efficient approximation of the values calculated on the basis of extension principle. © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2009.5342282

Approaching the fuzzy road transport Traveling Salesman Problem by eugenic bacterial memetic algorithm

J. Botzheim P. Földesi

Publication Name: Isciii 09 4th International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2009-12-28

Volume: Unknown

Issue: Unknown

Page Range: 15-22

Description:

The aim of the Traveling Salesman Problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities and returning to the starting point. In solutions presented in the literature costs of travel between nodes (cities) are based on Euclidean distances, the problem is symmetric and the costs are constant. In this paper a novel construction and formulation of the TSP is presented in which the requirements and features of practical application in road transportation and supply chains are taken into consideration. Computational results are presented as well. © 2009 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2009.5342281

Solution for fuzzy road transport traveling salesman problem using eugenic bacterial memetic algorithm

J. Botzheim P. Földesi L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1667-1672

Description:

The aim of the Traveling Salesman Problem (TSP) is to find the cheapest way of visiting all elements in a given set of cities and returning to the starting point. In solutions presented in the literature costs of travel between nodes (cities) are based on Euclidean distances, the problem is symmetric and the costs are constant. In this paper a novel construction and formulation of the TSP is presented in which the requirements and features of practical application in road transportation and supply chains are taken into consideration. Computational results are presented as well.

Open Access: Yes

DOI: DOI not available

Approximation of a modified traveling salesman problem using bacterial memetic algorithms

J. Botzheim P. Földesi Mark Farkas L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-12-01

Volume: 243

Issue: Unknown

Page Range: 607-625

Description:

The goal of this paper is to develop an algorithm that is capable to handle a slightly modified version of the minimal Traveling Salesman Problem in an efficient and robust way and produces high-quality solutions within a reasonable amount of time. The requirements of practical logistical applications, such as road transportation and supply chains, are also taken into consideration in this novel approach of the TSP. This well-known combinatorial optimization task is solved by a bacterial memetic algorithm, which is an evolutionary algorithm inspired by bacterial transduction. A new method is also proposed to deal with the time dependency in the cost matrix. The efficiency of the implementation, including time and space constraints, is investigated on a real life problem. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-03737-5_44

Comparative analysis of various evolutionary and memetic algorithms

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 10th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2009

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 193-205

Description:

Optimization methods known from the literature include gradient techniques and evolutionary algorithms. The main idea of gradient methods is to calculate the gradient of the objective function at the actual point and then to step towards better values according to this value. Evolutionary algorithms imitate a simplified abstract model of evolution observed in nature. Memetic algorithms traditionally combine evolutionary and gradient techniques to exploit the advantages of both methods. Our current research aims to discover the properties, especially the efficiency (i.e. the speed of convergence) of particular evolutionary and memetic algorithms. For this purpose the techniques are compared by applying them on several numerical optimization benchmark functions and on fuzzy rule base identification.

Open Access: Yes

DOI: DOI not available

Applying bacterial memetic algorithm for training feedforward and fuzzy flip-flop based neural networks

J. Botzheim László Gál A. E. Ruano L. T. Koczy

Publication Name: 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference Ifsa Eusflat 2009 Proceedings

Publication Date: 2009-12-01

Volume: Unknown

Issue: Unknown

Page Range: 1833-1838

Description:

In our previous work we proposed some extensions of the Levenberg-Marquardt algorithm; the Bacterial Memetic Algorithm and the Bacterial Memetic Algorithm with Modified Operator Execution Order for fuzzy rule base extraction from input-output data. Furthermore, we have investigated fuzzy flip-flop based feedforward neural networks. In this paper we introduce the adaptation of the Bacterial Memetic Algorithm with Modified Operator Execution Order for training feedforward and fuzzy flipflop based neural networks. We found that training these types of neural networks with the adaptation of the method we had used to train fuzzy rule bases had advantages over the conventional earlier methods.

Open Access: Yes

DOI: DOI not available

Fuzzy rule base model identification by bacterial memetic algorithms

J. Botzheim László Gál L. T. Koczy

Publication Name: Studies in Computational Intelligence

Publication Date: 2009-09-03

Volume: 222

Issue: Unknown

Page Range: 21-43

Description:

Fuzzy systems have been successfully used in the area of controllers for a long time. The Mamdani method is one of the most popular inference systems for practical applications. The main problem of Mamdani-type inference system and other fuzzy logic based controllers is how to gain the fuzzy rules the inference system based on. Several approaches have been proposed for automatic rule base identification. The bacterial type evolutionary algorithms have been successfully applied for solving this task. These algorithms are based on the Pseudo-Bacterial Genetic Algorithm and are supplied with operations and methods (e.g. the Levenberg-Marquardt method) to complete their task more efficiently. The goal is to create more accurate fuzzy rule bases from input-output data sets as quickly as possible. In this work, we summarize the bacterial type evolutionary algorithms used for fuzzy rule base identification. © 2009 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-02187-9_3

Fuzzy rule extraction by bacterial memetic algorithms

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: International Journal of Intelligent Systems

Publication Date: 2009-03-01

Volume: 24

Issue: 3

Page Range: 312-339

Description:

In our previous papers, fuzzy model identification methods were discussed. The bacterial evolutionary algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt method was also proposed for determining membership functions in fuzzy systems. The combination of the evolutionary and the gradient-based learning techniques is usually called memetic algorithm. In this paper, a new kind of memetic algorithm, the bacterial memetic algorithm., is introduced for fuzzy rule extraction. The paper presents how the bacterial evolutionary algorithm can be improved with the Levenberg-Marquardt technique. © 2009 Wiley Periodicals, Inc.

Open Access: Yes

DOI: 10.1002/int.20338

Comparison of fuzzy rule-based learning and inference systems

J. Botzheim Krisztián Balázs L. T. Koczy

Publication Name: 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2008

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 61-75

Description:

In our work we have compared various fuzzy rule based learning and inference systems. The base of the investigations was a modular system that we have implemented in C language. It contains several alternative versions of the two key elements of rule based learning - namely, the optimization algorithm and the inference method - which can be found in the literature. We obtained very different properties when combining these alternatives (changing the modules and connecting them) in all possible ways. The investigations determined the values of the quality measures (complexity and accuracy) of the obtained alternatives both analitically and experimentally where it was possible. Based on these quality measures the combinations have been ordered according to different aspects.

Open Access: Yes

DOI: DOI not available

Modified bacterial memetic algorithm used for fuzzy rule base extraction

J. Botzheim László Gál L. T. Koczy

Publication Name: 5th International Conference on Soft Computing as Transdisciplinary Science and Technology Cstst 08 Proceedings

Publication Date: 2008-12-01

Volume: Unknown

Issue: Unknown

Page Range: 425-431

Description:

In this paper we discuss an improved version of the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. In previous works we have found several ways to improve the original BMA. Some of them perform well rather in the case of more complex fuzzy rule base, and some of them perform well rather in the case of less complex fuzzy rule base. We have combined the improvements into a new version of the BMA that performs well in each case investigated. Copyright 2008 ACM.

Open Access: Yes

DOI: 10.1145/1456223.1456310

Improvements to the bacterial memetic algorithm used for fuzzy rule base extraction

J. Botzheim László Gál L. T. Koczy

Publication Name: Cimsa 2008 IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings

Publication Date: 2008-09-26

Volume: Unknown

Issue: Unknown

Page Range: 38-43

Description:

In this paper we discuss new methods to improve the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. The first two methods are knot order violation handling methods which improves the performance of the BMA rather in the case of more complex fuzzy rule base. The third method is a new modification of the BMA in which the order of the operators is modified. This method improves the performance of the BMA rather in the case of less complex fuzzy rule base. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/CIMSA.2008.4595829

Fuzzy solution for non-linear quality models

J. Botzheim P. Földesi L. T. Koczy

Publication Name: 12th International Conference on Intelligent Engineering Systems Proceedings Ines 2008

Publication Date: 2008-09-01

Volume: Unknown

Issue: Unknown

Page Range: 269-275

Description:

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target is to achieve maximum customer satisfaction within given financial limits. Kano's quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a non-linear relationship to satisfaction, rather power-function should be used. For the customers' subjective evaluation these relationships are not deterministic and are uncertain. This paper proposes a method for fuzzy extension of Kano's model and presents numerical examples that can prove the efficiency of bacterial evolutionary algorithm in as well. © 2008 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2008.4481306

Fuzzy rule base extraction by the improved bacterial memetic algorithm

J. Botzheim László Gál A. E. Ruano L. T. Koczy

Publication Name: Sami 2008 6th International Symposium on Applied Machine Intelligence and Informatics Proceedings

Publication Date: 2008-08-25

Volume: Unknown

Issue: Unknown

Page Range: 49-53

Description:

In this paper we introduce new methods for handling knot order violation occurred in the Bacterial Memetic Algorithm (BMA) used for fuzzy rule base extraction. These methods perform slightly better than the method used before and are easier to integrate with the Bacterial Memetic Algorithm. ©2008 IEEE.

Open Access: Yes

DOI: 10.1109/SAMI.2008.4469132

Grooming-enhanced multicast in multilayer networks with bacterial evolutionary algorithm

J. Botzheim Péter Soproni Tibor Cinkler L. T. Koczy

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics Cinti 2007

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: 211-225

Description:

In this paper we introduce new, bacterial evolutionary algorithm (BEA) based methods for routing unicast and multicast demands in grooming capable multi-layer optical wavelength division multiplexing (WDM) networks. The methods introduced are compared with both well known heuristic methods, accumulative shortest path heuristic (ASP) and minimum path heuristic (MPH), and as well as with ILP. We prove the strength of our approach by comprehensive simulations in our versatile simulator.

Open Access: Yes

DOI: DOI not available

Increasing diagnostic accuracy by meta optimization of fuzzy rule bases

J. Botzheim Mario Drobics L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2007-12-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In medicine the decision on which test to choose for a given decision problem is a delicate problem. On the one hand a positive test should be a reliable indicator on the presence of a disease, while on the other hand a negative test is required to be an indicator on the absence of a disease. Of course, these two goals are conflicting and a balanced decision according to the current situation is required. Inductive learning methods for (fuzzy) rule bases are, however, typically not capable of optimizing such complex and problem depending goal functions. We therefore present a meta-learning algorithm which selects a subset from a previously generated set of fuzzy rules using bacterial evolutionary algorithms. We also present a study where the proposed method is used to generate a model for predicting the presence/absence of hepatitis, based on laboratory results. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2007.4295377

Fuzzy models and interpolation

J. Botzheim T. D. Gedeon L. T. Koczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2007-10-08

Volume: 217

Issue: Unknown

Page Range: 111-131

Description:

This paper focuses on two essential topics of the fuzzy area. The first is the reduction of fuzzy rule bases. The classical inference methods of fuzzy systems deal with dense rule bases where the universe of discourse is fully covered. By applying sparse or hierarchical rule bases the computational complexity can be decreased. The second subject of the paper is the introduction of some fuzzy rule base identification techniques. In some cases the fuzzy rule base might be given by a human expert, but usually there are only numerical patterns available and an automatic method has to be applied to determine the fuzzy rules. © 2007 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-540-73182-5_6

Fuzzy extension for Kano's model using bacterial evolutionary algorithm

J. Botzheim P. Földesi L. T. Koczy

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 147-151

Description:

For designing and developing products/services it is vital to know the relevancy of the performance generated by each technical attribute and how they can increase customer satisfaction. Improving the parameters of technical attributes requires financial resources, and the budgets are generally limited. Thus the optimum target is to achieve maximum customer satisfaction within given financial limits. Kano's quality model classifies the relationships between customer satisfaction and attribute-level performance and indicates that some of the attributes have a nonlinear relationship to satisfaction, rather power-function should be used. For the customers' subjective evaluation these relationships are not deterministic and are uncertain. This paper proposes a method for fuzzy extension of Kano's model and presents numerical examples that can prove the efficiency of bacterial evolutionary algorithm in as well. © 2007 IEEE.

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367379

Genetic and Bacterial Programming for B-Spline Neural Networks Design

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2007-03-01

Volume: 11

Issue: 2

Page Range: 220-231

Description:

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Open Access: Yes

DOI: 10.20965/jaciii.2007.p0220

Separated antecedent and consequent learning for Takagi-Sugeno fuzzy systems

J. Botzheim T. D. Gedeon Erich Peter Klement Edwin Lughofer L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2006-12-01

Volume: Unknown

Issue: Unknown

Page Range: 2263-2269

Description:

In this paper a new algorithm for the learning of Takagi-Sugeno fuzzy systems is introduced. In the algorithm different learning techniques are applied for the antecedent and the consequent parameters of the fuzzy system. We propose a hybrid method for the antecedent parameters learning based on the combination of the Bacterial Evolutionary Algorithm (BEA) and the Levenberg-Marquardt (LM) method. For the linear parameters in fuzzy systems appearing in the rule consequents the Least Squares (LS) and the Recursive Least Squares (RLS) techniques are applied, which will lead to a global optimal solution of linear parameter vectors in the least squares sense. Therefore a better performance can be guaranteed than with a complete learning by BEA and LM. The paper is concluded by evaluation results based on high-dimensional test data. These evaluation results compare the new method with some conventional fuzzy training methods with respect to approximation accuracy and model complexity. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/FUZZY.2006.1682014

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

J. Botzheim B. Sumudu U. Mendis T. D. Gedeon L. T. Koczy

Publication Name: Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical Fuzzy Signature Structures. In this paper, we further generalise the weights and the aggregation into a new operator called Weighted Relevance Aggregation Operator (WRAO). WRAO enhances the adaptability of the fuzzy signature model to different applications and simplifies the learning of fuzzy signature models from data. We also show the methodology of learning these aggregation operators from data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/CIMCA.2006.110

Bacterial memetic algorithm for fuzzy rule base optimization

C. Cabrita J. Botzheim T. D. Gedeon Carlos Fonseca A. E. Ruano L. T. Koczy

Publication Name: 2006 World Automation Congress Wac 06

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base. Copyright - World Automation Congress (WAC) 2006.

Open Access: Yes

DOI: 10.1109/WAC.2006.376057

Fuzzy models, identification and applications

J. Botzheim L. T. Koczy

Publication Name: Iccc 2005 IEEE 3rd International Conference on Computational Cybernetics Proceedings

Publication Date: 2005-12-01

Volume: 2005

Issue: Unknown

Page Range: 13-19

Description:

This paper gives a brief overview of fuzzy model identification techniques. The paper discusses how the membership functions of a fuzzy system can be extracted from an input/output data (pattern) set without human interference. There are several methods used for rule extraction known from the literature. The bacterial algorithm is an evolutionary technique that was inspired by the microbial evolution phenomenon. The Levenberg-Marquardt algorithm is an advanced gradient type optimization method that has been developed initially for neural networks and is introduced here for the optimization of the fuzzy rule base. Fuzzy clustering is presented also as another alternative way for the rule extraction. In the part describing the model the fuzzy rule interpolation method and the approach of hierarchical rule bases are introduced. Combining fuzzy rule interpolation with the use of hierarchically structured fuzzy rule bases leads to the reduction of the fuzzy algorithms' complexity. Hierarchical fuzzy modeling by clustering techniques is also introduced in the paper.

Open Access: Yes

DOI: 10.1109/ICCCYB.2005.1511538

An hybrid training method for B-spline neural networks

C. Cabrita J. Botzheim A. E. Ruano L. T. Koczy

Publication Name: 2005 IEEE International Workshop on Intelligent Signal Processing Proceedings

Publication Date: 2005-12-01

Volume: Unknown

Issue: Unknown

Page Range: 165-170

Description:

Current and past research has brought up new views related to the optimization of neural networks. For a fixed structure, second order methods are seen as the most promising. From previous works we have shown how second order methods are of easy applicability to a neural network. Namely, we have proved how the Levenberg-Marquard possesses not only better convergence but how it can assure the convergence to a local minima. However, as any gradient-based method, the results obtained depend on the startup point. In this work, a reformulated Evolutionary algorithm - the Bacterial Programming for Levenberg-Marquardt is proposed, as an heuristic which can be used to determine the most suitable starting points, therefore achieving, in most cases, the global optimum. © 2005 IEEE.

Open Access: Yes

DOI: DOI not available

Design of B-spline neural networks using a bacterial programming approach

C. Cabrita J. Botzheim A. E. Ruano L. T. Koczy

Publication Name: IEEE International Conference on Neural Networks Conference Proceedings

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 2313-2318

Description:

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In this paper a new technique, Bacterial Programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

Open Access: Yes

DOI: 10.1109/IJCNN.2004.1380987

Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

J. Botzheim C. Cabrita A. E. Ruano L. T. Koczy

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2004-12-01

Volume: 3

Issue: Unknown

Page Range: 1667-1672

Description:

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear functions as well.

Open Access: Yes

DOI: 10.1109/FUZZY.2004.1375431