Multi-objective Modeling and Optimization of Building External Walls Using Genetic Algorithm and Simulated Annealing

This research proposes an optimized structure for building exterior walls to achieve standard thermal resistance while minimizing total thickness and weight. To address this, two metaheuristic algorithms, namely the Genetic Algorithm (GA) and Simulated Annealing (SA), have been employed. The model is developed based on a dataset of real construction materials and considers three-layer wall panels that incorporate both thermal and constructional constraints. The defined optimization objectives include meeting the specified thermal resistance requirements, minimizing wall thickness, and reducing total weight. A comparative analysis of the results indicates that the Genetic Algorithm demonstrates higher accuracy in attaining the target thermal resistance and explores a wider variety of materials. Conversely, the Simulated Annealing algorithm exhibits a tendency towards favoring lightweight materials and utilizes a smaller selection of material types for panel design. These findings highlight the potential of employing intelligent optimization algorithms in designing material combinations for building applications, offering effective thermal performance and enhanced flexibility on thermal resistance design of walls.

کلیدواژه ها:

Building Envelope ، Energy Optimization ، Genetic Algorithm ، Prescriptive Approach ، Simulated Annealing