Optimal Modeling of Construction Waste Management Using Metaheuristic Algorithms with an Environmental Preservation Approach

Construction waste management is one of the fundamental challenges in the construction industry, with significant economic and environmental impacts. This study presents a multi-objective optimization model for construction waste management, simultaneously considering the objectives of minimizing total cost, reducing CO₂ emissions, and optimizing collection and transportation time. Sample data were collected from residential, commercial, and infrastructure projects, and metaheuristic algorithms—including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a hybrid GA–PSO algorithm—were employed to solve the model. The results indicate that the PSO and GA–PSO algorithms were able to reduce costs, CO₂ emissions, and collection time compared to GA, with an optimal recycling rate ranging between ۷۰–۷۶%. Sensitivity analysis emphasizes that increasing the recycling rate and reducing the distance to recycling centers play a key role in mitigating economic and environmental impacts. The findings demonstrate that the proposed model can serve as a practical and effective tool for project managers and waste management organizations and aligns with the principles of a circular economy.

کلیدواژه ها:

Construction waste ، multi-objective optimization ، metaheuristic algorithms ، particle swarm optimization ، genetic algorithm ، recycling rate ، emission reduction