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.

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.