Integrating Recycling and Emission Reduction: A Business Strategy Analysis With Multi‐Objective Mixed‐Integer Linear Programming Framework for Optimising Sustainable Closed‐Loop Supply Chain Network Design
研究开发了一个混合整数线性规划模型，用于优化闭环供应链网络设计，平衡利润、供应商质量和减排目标，发现多目标粒子群优化方法在求解速度和方案质量上优于NSGA-II，为可持续运营管理决策提供支持。
ABSTRACT This research develops an integrated mixed‐integer linear programming (MILP) model for closed‐loop supply chain network design that optimises competing economic and environmental objectives including profit maximisation, supplier quality improvement and CO 2 emission reduction. The primary aim of this study is to identify which solution techniques perform best when dealing with different sizes of problems. The multi‐objective particle swarm optimisation (MOPSO) method demonstrated superior performance over NSGA‐II by achieving 35%–45% faster convergence rates and delivering 20%–30% better solution quality. The epsilon‐constraint approach with CPLEX showed better performance for solving smaller problems. The analysis revealed that return rates, together with material recovery expenses, function as essential elements which determine the profitability of the disassembly process. The research proves that multi‐objective optimisation methods work efficiently with real supply chain sizes. These findings support the development of decision support systems for sustainable operations management.