Pareto Ant Colony Algorithm for Building Life Cycle Energy Consumption Optimization
This article aims at realizing optimal building energy consumption in its whole life cycle, and develops building life cycle energy consumption model (BLCECM), as well as optimizes the model by Ant Colony Algorithm (ACA). Aiming at the complexity and multi-objective principle of building life cycle energy consumption, this research tries to modify Pareto Ant Colony Algorithm (PACA), making it fit the needs of finding solution to least energy consumption in a building’s whole life cycle. In the initial stage of ant colony constructing solution, each objective weighing is defined randomly, which improves the optimal determination mechanism of Pareto solution, perfects the renovation principle of pheromone, and finally realize the goal of optimization. This research is a innovative application of ACA in building energy-saving area, and it provides definite as well as practical calculation method for building energy consumption optimization in terms of a whole life cycle.
Keywordsant colony algorithm building life cycle building energy consumption multi-objective optimization
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- 2.The Weidt Group: Integrated cost-estimation methodology to support high-performance building design. Energy Efficiency 2(1), 69–85 (2009)Google Scholar
- 3.Gu, D., Zhu, Y., Gu, L.: Life cycle assessment for China building environment impacts. Journal of Tsinghua University 46(12), 1953–1956 (2006)Google Scholar
- 4.Coloni, D.M., Maniezzo, V., et al.: Distributed Optimization by Ant Colonies. In: Proceedings of European Conference on Artificial Life, Paris, France, pp. 134–142 (1991)Google Scholar