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A Hybrid Butterfly-Genetic Algorithm for Sustainable Closed-Loop Supply Chain Network Design with Pricing Consideration: An Application to the Home Appliance Industry
Maria Moghadam1 , Iraj Mahdavi2 , Ali Tajdin3 , Babak Shirazi3
1- Ph.D. Student in Industrial Engineering, Faculty of Industrial Engineering, Mazandaran University of Science and Technology
2- Faculty Member of the Faculty of Industrial Engineering, Mazandaran University of Science and Technology , irajarash@ustmb.ac.ir
3- Faculty Member of the Faculty of Industrial Engineering, Mazandaran University of Science and Technology
Abstract:   (17 Views)
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.
Keywords: Closed Loop Supply Chain, Sustainability, Metaheuristic Algorithm, Genetic Algorithm, Butterfly Optimization Algorithm, Home Appliance Industry, Reverse Logistics, Multi Objective Optimization
Full-Text [PDF 889 kb]   (10 Downloads)    
Type of Study: Research | Subject: Optimization Techniques
Received: 2026/05/31 | Accepted: 2026/10/4
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.