Design of Multi-Objective Optimization System for Construction Engineering Under BIM and Genetic Algorithm

Previous studies have often focused on optimizing a single objective, such as cost reduction or shortened project timelines. This single objective optimization method may overlook other key factors such as sustain ability, quality, and safety, leading to poor overall project performance. This article utilizes building information modeling (BIM) technology to integrate various aspects of construction project information, and introduces multi-objective optimization techniques such as genetic algorithm (GA). At the same time, this article considers multiple objectives such as cost, duration, and sustainability to balance the relationship between different objectives and optimize overall project performance. It collects information related to construction projects, including data from various stages such as design, construction, and operation. The design optimization goals are: cost optimization, schedule optimization, sustain ability optimization, and quality optimization. This article uses BIM to create a three-dimensional model of a building and combines genetic algorithms for architectural design optimization. The experimental results show that the average cost of BIM-GA is 2365.7 yuan/square meter, and the combination of BIM and genetic algorithm can effectively shorten the construction period.