For any country, the availability of electricity is crucial to the development of the national economy and society. As a result, decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system. This research aims to provide a multi-criterion decision-making (MCDM) method for assessing the sustainability and security of the electrical supply. The weights of criteria, which indicate their relative relevance in the assessment of the sustainability and security of the energy supply, the MCDM method allow users to express their opinions. To overcome the impact of uncertainty and vagueness of expert opinion, we explore the notion of picture fuzzy theory, which is a more efficient and dominant mathematical model. Recently, the theory of Aczel-Alsina operations has attained a lot of attraction and has an extensive capability to acquire smooth approximated results during the aggregation process. However, Choquet integral operators are more flexible and are used to express correlation among different attributes. This article diagnoses an innovative theory of picture fuzzy set to derive robust mathematical methodologies of picture fuzzy Choquet Integral Aczel-Alsina aggregation operators. To prove the intensity and validity of invented approaches, some dominant properties and special cases are also discussed. An intelligent decision algorithm for the MCDM problem is designed to resolve complicated real-life applications under multiple conflicting criteria. Additionally, we discussed a numerical example to investigate a suitable electric transformer under consideration of different beneficial key criteria. A comparative study is established to capture the superiority and effectiveness of pioneered mathematical approaches with existing methodologies.

The automobile industry plays a pivotal role in global economic development, technological innovation, and sustainable mobility solutions. It drives advancements in engineering, manufacturing, and smart technologies and influences transportation systems. A decision analysis system in the automobile industry serves as a structured framework to evaluate complex choices involving design, production, supply chain, marketing, and sustainability strategies based on vague human information. To achieve the main goal of this article, we explore the concepts of spherical fuzzy sets (SFSs) for handling uncertainty and vagueness in human judgments. The SFS is a more efficient and broader fuzzy framework that has extensive information about an object. Besides the concepts discussed in the fuzzy framework, we also modify the theory of Hamy mean (HM) models under Aczel Alsina operations. By combining two different theories of Aczel Alsina operations and Hamy mean models, we derive a family of mathematical models, namely spherical fuzzy Aczel Alsina Hamy mean (SFAHM) and spherical fuzzy Aczel Alsina weighted Hamy mean (SFAWHM) operators. Moreover, another generalization of the Dual HM (DHM) models is modified in the form of spherical fuzzy Aczel Alsina DHM (SFADHM) and spherical fuzzy Aczel Alsina weighted DHM (SFAWDHM) operators. Some reliable and appropriate characteristics are also studied to demonstrate the flexibility of the proposed operators. An intelligent decision algorithm of the multi-attribute group decision-making (MAGDM) problem is discussed to resolve real-life applications and a group of expert’s opinions. To see the effectiveness and reliability of newly developed terminologies, we discussed a numerical example to choose desirable alternatives under an automobile industry system. The influence study is also presented here by setting numerous parametric values in the currently discussed methodologies. To showcase the validation and superiority of diagnosed mathematical models, we establish a comparative study to compare the results of invented approaches with the results of existing terminologies.

Waste management is a crucial and significant subject that has gained much attention globally because it has several environmental, social, financial and economic implications. Solid waste management is a very challenging task for clean urban and rural societies. We studied some reliable strategies for handling the waste materials and garbage produced by people. To serve this purpose, an intuitionistic fuzzy set (IFS) is a well-known model used for modeling and processing unpredictable information and providing accurate approximated results in the decision-making process. Power average operators allow the interrelationship of the input arguments and deal with uncertain information in complicated situations. This article expresses Sugeno-weber triangular norms under intuitionistic fuzzy (IF) information. We developed a class of new aggregation operators, including intuitionistic fuzzy Sugeno-Weber power-weighted average (IFSWPWA) and intuitionistic fuzzy Sugeno-Weber power-weighted geometric (IFSWPWG) operators. It is observed that both the newly proposed operators satisfy the properties of aggregation. The multi-criteria decision-making (MCDM) problem is proposed to evaluate real-life applications and numerical examples. An experimental case study under the system of waste materials is considered in the article to reveal the intensity and applicability of derived approaches. The comparison analysis and sensitivity analysis show the significance of our proposed work.

A multi-robotic task assignment and decision analysis system refers to an advanced framework in robotics and artificial intelligence where multiple robots are coordinated to perform a set of tasks efficiently and intelligently. This article designs innovative approaches to fix uncertainty during task allocation in a multi-robotic system under a hybrid fuzzy framework and decision-making models. To achieve this goal, we expose a modified theory of circular q-rung orthopair fuzzy set (Crq-ROFS), which is a broader framework of intuitionistic fuzzy sets and q-rung orthopair fuzzy sets. We formulated feasible operations of Schweizer-Sklar t-norm and t-conorm in light of circular information about q-rug orthopair fuzzy (Crq-ROF). We also delved into a family of mathematical approaches of Schweizer-Sklar t-norm and t-conorm, namely, Crq-ROF Schweizer-Sklar weighted average (Crq-ROFSSWA) and Crq-ROF Schweizer-Sklar weighted geometric (Crq-ROFSSWG) operators with dominant propositions. The theory of the multi-attribute decision-making (MADM) problem offers authentic and reliable solutions by aggregating human judgment. An experimental case study discussed evaluating an ideal solution under consideration of multi-criteria or attribute information. A comparison method is conducted to showcase the reliability and effectiveness of the pioneering approaches with existing approaches.