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

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.

[1]  László T. Kóczy,et al.  Comparative Investigation of Various Evolutionary and Memetic Algorithms , 2010 .

[2]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[3]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

[4]  Leslie K. Norford,et al.  Genetic Algorithms for Optimization of Building Envelopes and the Design and Control of HVAC Systems , 2003 .

[5]  Supatcharawadee Pornkrisadanuphan A Genetic Algorithm-Based Approach Design for Energy-Efficient Building in Thailand , .

[6]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[7]  László T. Kóczy,et al.  Fuzzy rule extraction by bacterial memetic algorithms , 2009, Int. J. Intell. Syst..

[8]  Xiaowei Tan A parametric building energy cost optimization tool based on a genetic algorithm , 2007 .

[9]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[10]  László T. Kóczy,et al.  Eugenic bacterial memetic algorithm for fuzzy road transport traveling salesman problem , 2011 .

[11]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[12]  Naoyuki Kubota,et al.  Bacterial memetic algorithm for offline path planning of mobile robots , 2012, Memetic Comput..

[13]  Takeshi Furuhashi,et al.  Fuzzy system parameters discovery by bacterial evolutionary algorithm , 1999, IEEE Trans. Fuzzy Syst..

[14]  Andreas H. Hermelink,et al.  A Retrofit for Sustainability: Meeting Occupants' Needs within Environmental Limits , 2006 .

[15]  D. ürge-Vorsatz,et al.  Potentials and costs of carbon dioxide mitigation in the world's buildings , 2008 .