An improved multi-objective ant colony algorithm for building life cycle energy consumption optimisation

Authors:
Yan Yuan;Jingling Yuan;Hongfu Du;Li Li
Affiliations:
School of Urban Design, Wuhan University, Luojia Hill, Wuhan, 430072, China.;Computer Science and Technology School, Wuhan University of Technology, 122 Luoshi Road, Wuhan, 430070, China.;Computer Science and Technology School, Wuhan University of Technology, 122 Luoshi Road, Wuhan, 430070, China.;School of Urban Design, Wuhan University, Luojia Hill, Wuhan, 430072, China
Venue:
International Journal of Computer Applications in Technology
Year:
2012

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Abstract

Building energy consumption (BEC) is very important for the environmental sustainability. Because of complexity and variety of building energy consumption, to achieve building energy consumption optimisation, especially for building life-cycle (BLC), multiple objectives have to be satisfied. In this paper, a novel mathematical model for BLC energy consumption assessment is formalised, a novel algorithm for optimisation of BLC energy consumption is developed by improving the multi-objective ant colony optimisation (MACO). In the algorithm, the estimation mechanism of Pareto optimal solution and the update rule of pheromone are derived. An efficacious optimisation solution for BLC energy consumption and an innovative application of MACO algorithm in the building energy efficiency area are presented in the paper.