An Innovative Multicriteria Decision-Making Tool for Building Performance Optimization

Résumé

Buildings are accountable for nearly 40% of global greenhouse gas emissions. Their overall efficiency is thus a major pillar to optimize energy consumption and to mitigate engendered global warming. The current work takes part in this global dynamic. Indeed, we developed a standalone decision-aid tool based on sensitivity analysis, multiobjective optimization, and artificial neural networks to design a new generation of energy-efficient buildings. The tool aims to allow benefiting from Sobol’ sensitivity analysis samplings to instantaneously generate sensitivity indexes and perform multicriteria optimizations. This efficient process allows both understanding buildings’ complex behavior (by ranking the impact of the inputs parameters on the outputs and highlighting their interactions) and optimizing their overall performance. The main advantages of this method are the time gaining and the provision of relevant outputs to analyze the buildings’ design. The tool was successfully used to solve constrained 13-input parameters with 5-criteria on TRNSYS simulation program, considering the impact of global warming

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