Multi-Objective Techno-Economic Optimization of Design Parameters for Residential Buildings in Different Climate Zones

The comprehensive approach for a building envelope design involves performance simulations, which are time-consuming and require knowledge of complicated processes. In addition, climate variation makes the selection these parameters more complex. paper aims to establish guidelines determining single-family household’s unique optimal passive in various zones worldwide. For this purpose, bi-objective optimization is performed twenty-four locations twenty climates by coupling TRNSYS non-dominated sorting genetic algorithm (NSGA-III) using Python program. process generates Pareto fronts thermal load investment cost identify optimum options insulation level envelope, window aperture cooling, window-to-wall ratio (WWR), shading fraction, radiation-based control, orientation. goal find feasible trade-off between energy demand insulation. This achieved multi-criteria decision making (MCDM) through criteria importance intercriteria correlation (CRITIC) technique order preference similarity ideal solution (TOPSIS). results demonstrate that an remarkably improves compared base case previous practices. However, weather conditions strongly influence parameters. research findings set benchmark energy-efficient household envelopes investigated climates. sets also provide criterion selecting ranges according space heating cooling demands zone.