Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Advanced Engineering Informatics
Automatic design synthesis and optimization of component-based systems by evolutionary algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Hype: An algorithm for fast hypervolume-based many-objective optimization
Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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In this on-going work, we aim at contributing to the issue of energy consumption by proposing tools to automatically define some aspects of the architectural and structural design of buildings. Our framework starts with a building design, and automatically optimizes it, providing to the architect many variations that minimize, in different ways, both energy consumption and construction costs. The optimization stage is done by the combination of an energy consumption simulation program, EnergyPlus, with a state-of-the-art multi-objective evolutionary algorithm, Hype. The latter explores the design search space, automatically generating new feasible design solutions, which are then evaluated by the energy simulation software. Preliminary results are presented, in which the proposed framework is used to optimize the orientation angle of a given commercial building and the materials used for the thermal insulation of its walls.