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Physarum solver: a bio-inspired method for sustainable supply chain network design problem

Author

Listed:
  • Xiaoge Zhang

    (Southwest University
    Vanderbilt University)

  • Andrew Adamatzky

    (University of the West of England)

  • Felix T. S. Chan

    (Hong Kong Polytechnic University)

  • Sankaran Mahadevan

    (Southwest University)

  • Yong Deng

    (Southwest University
    Vanderbilt University)

Abstract

A supplier of products and services aims to minimize the capacity investment cost and the operational cost incurred by unwanted byproducts, e.g. carbon dioxide emission. In this paper, we consider a sustainable supply chain network design problem, where the capacity and the product flow along each link are design variables. We formulate it as a multi-criteria optimization problem. A bio-inspired algorithm is developed to tackle this problem. We illustrate how to design a sustainable supply chain network in three steps. First, we develop a generalized model inspired by the foraging behaviour of slime mould Physarum polycephalum to handle the network optimization with multiple sinks. Second, we propose a strategy to update the link cost iteratively, thus making the Physarum model to converge to a user equilibrium. Third, we perform an equivalent operation to transform a system optimum problem into a corresponding user equilibrium problem so that it is solvable in the Physarum model. The efficiency of the proposed algorithm is illustrated with numerical examples.

Suggested Citation

  • Xiaoge Zhang & Andrew Adamatzky & Felix T. S. Chan & Sankaran Mahadevan & Yong Deng, 2017. "Physarum solver: a bio-inspired method for sustainable supply chain network design problem," Annals of Operations Research, Springer, vol. 254(1), pages 533-552, July.
  • Handle: RePEc:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2410-x
    DOI: 10.1007/s10479-017-2410-x
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    References listed on IDEAS

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    Cited by:

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    2. Xiaofeng Lv & Deyun Zhou & Yongchuan Tang & Ling Ma, 2018. "An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    3. Masoud Rabbani & Ali Sabbaghnia & Mahdi Mobini & Jafar Razmi, 2020. "A graph theory-based algorithm for a multi-echelon multi-period responsive supply chain network design with lateral-transshipments," Operational Research, Springer, vol. 20(4), pages 2497-2517, December.

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