نشریه بین المللی مهندسی صنایع و تحقیقات تولید
دانشگاه علم و صنعت ایران
چهارشنبه 15 مهر 1405
[Archive]
چکیده: (16 مشاهده)
This article addresses the mounting pressure on industries to adopt sustainable practices by first developing a multi-echelon, multi-product, and multi-period closed-loop supply chain network model that integrates forward and reverse logistics for the home appliance sector. The model jointly pursues three objectives, namely economic efficiency, environmental impact, and social responsibility, combined into a single weighted fitness function, and explicitly differentiates pricing between original and remanufactured products. To solve the resulting large-scale mixed integer linear program, a novel hybrid metaheuristic algorithm is then proposed, embedding the crossover and mutation operators of the genetic algorithm (GA) into the butterfly optimization algorithm (BOA) to strengthen exploration of the search space and curb premature convergence. The hybrid algorithm, the GA, and the BOA are compared on six test problems of increasing size. Across these instances, the hybrid algorithm consistently outperforms the two standalone algorithms, improving the normalized revenue, environmental, and social criteria while reducing the normalized cost, with changes of up to about 0.05-0.10 (on a 0-1 normalized scale) relative to the BOA and the GA respectively; a sensitivity analysis on the objective weights further confirms the stability of these gains. These results demonstrate the superior solution quality of the hybrid metaheuristic algorithm and underline the importance of jointly addressing economic, environmental, and social objectives in closed-loop supply chain design. By contributing both an integrated sustainable network model and an efficient solution method, this study supports the adoption of closed-loop supply chain practices that reduce environmental footprints and promote social responsibility in the home appliance industry.
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