Optimization of Urban Building Energy Performance through Architectural Design Based on Genetic Algorithms

With the escalating energy consumption in urban buildings and the consequent environmental impacts, the adoption of advanced energy optimization methods in architectural design has become imperative. This study focuses on enhancing the energy performance of urban buildings through architecture design optimization based on genetic algorithms. Initially, key parameters influencing building energy consumption including geometric form, orientation, fenestration placement, and material properties were systematically modeled. These parameters were then encoded as decision variables within a genetic algorithm framework to intelligently and efficiently explore a vast design solution space. The primary objective was to minimize heating and cooling energy demands under various urban climatic conditions. By integrating numerical energy simulation with the genetic algorithm, multiple generations of optimized architectural solutions were generated and evaluated. The results demonstrate that this approach significantly improves building energy performance and offers effective strategies for sustainable, low-energy architectural design. This methodology enables architects to make informed design decisions in early stages while preserving functional and aesthetic requirements, ultimately contributing to the creation of buildings with optimized energy consumption and reduced environmental footprint.

کلیدواژه ها:

Genetic algorithm ، energy optimization ، architectural design ، urban buildings ، energy simulation