Hybrid NSGA-III and simulated annealing approach for multi-objective time–cost-quality-sustainability optimization in wastewater treatment plant construction projects

Abstract

The construction of wastewater treatment plants (WWTPs) involves complex trade-offs among time, cost, quality, and sustainability. This study proposes a hybrid NSGA-III and Simulated Annealing (SA) approach to optimize these conflicting objectives in WWTP construction projects. The multi-objective optimization model considers four objectives: (1) minimizing total project duration, (2) minimizing total project cost, (3) maximizing project quality, and (4) maximizing project sustainability. The problem is formulated as a multi-mode resource-constrained project scheduling problem (MRCPSP) with real-world constraints such as budget limits, project deadlines, and activity dependencies. The hybrid NSGA-III and SA algorithm enhances solution diversity and convergence efficiency, overcoming limitations of traditional metaheuristic methods. A case study on a WWTP project is conducted, where multiple Pareto-optimal solutions are obtained and analyzed. A Weighted Sum Method is used to select the most balanced trade-off solution. Results demonstrate that the proposed hybrid approach outperforms conventional optimization algorithms in terms of solution quality, hypervolume, and computational efficiency. A comparative analysis with existing models highlights its superior performance in balancing trade-offs in large-scale construction projects. This research contributes to the field of sustainable infrastructure development by integrating optimization techniques that support efficient decision-making in WWTP construction.