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Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm

Author

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  • Sonu Rajak

    (Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tiruchirappalli, India)

  • P. Parthiban

    (Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tiruchirappalli, India)

  • R. Dhanalakshmi

    (Department of Computer Science and Engineering, National Institute of Technology, Nagaland, Dimapur, India)

Abstract

This article presents a closed-loop supply chain (CLSC) network design problem consisting of both forward and reverse material flows. Here, a four-echelon single-product system is introduced in which multiple transportation channels are considered between the nodes of each echelon. Each design is analyzed for the optimum cost, time and environmental impact which form objective functions. The problem is modeled as a tri-objective mixed integer linear programming (MILP) model. The cost objective aggregates the opening cost (fixed cost) and the variable costs in both forward and reverses material flow. The time objective considers the longest transportation time from plants to customers and reverse. Factors of environmental impact are categorized and weighed using an analytic network process (ANP) which forms the environmental objective function. A genetic algorithm (GA) has been applied as a solution methodology to solve the MILP model. Ultimately, a case problem is also used to illustrate the model developed and concluding remarks are made regarding the results.

Suggested Citation

  • Sonu Rajak & P. Parthiban & R. Dhanalakshmi, 2018. "Selection of Transportation Channels in Closed-Loop Supply Chain Using Meta-Heuristic Algorithm," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 11(3), pages 64-86, July.
    • Handle: RePEc:igg:jisscm:v:11:y:2018:i:3:p:64-86
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    Cited by:

    1. Luttiely Santos Oliveira & Ricardo Luiz Machado, 2021. "Application of optimization methods in the closed-loop supply chain: a literature review," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 357-400, February.
    2. Sonu Rajak & K. E. K. Vimal & Sricharan Arumugam & Jagadesan Parthiban & Swesh Kannan Sivaraman & Jayakrishna Kandasamy & Angel Acevedo Duque, 2022. "Multi-objective mixed-integer linear optimization model for sustainable closed-loop supply chain network: a case study on remanufacturing steering column," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6481-6507, May.
    3. Wei Zhou & Chao Ke, 2022. "A Mass-Customization-Based Remanufacturing Scheme Design Method for Used Products," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    4. Yong Chen & Zhengjie Wu & Wenchao Yi & Bingjia Wang & Jianhua Yao & Zhi Pei & Jiaoliao Chen, 2022. "Bibliometric Method for Manufacturing Servitization: A Review and Future Research Directions," Sustainability, MDPI, vol. 14(14), pages 1-26, July.

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