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Weighing Efficiency-Robustness in Supply Chain Disruption by Multi-Objective Firefly Algorithm

Author

Listed:
  • Tong Shu

    (Business School, Hunan University, Changsha 410082, China)

  • Xiaoqin Gao

    (Business School, Hunan University, Changsha 410082, China)

  • Shou Chen

    (Business School, Hunan University, Changsha 410082, China)

  • Shouyang Wang

    (Business School, Hunan University, Changsha 410082, China
    Academy of Mathematics and System Science, Chinese Academy of Sciences, Beijing 100190, China)

  • Kin Keung Lai

    (International Business School, Shaanxi Normal University, Xi’an 710062, China
    Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue Kowloon, Hong Kong, China)

  • Lu Gan

    (Office of Humanities and Social Sciences, Hunan University, Changsha 410082, China)

Abstract

This paper investigates various supply chain disruptions in terms of scenario planning, including node disruption and chain disruption; namely, disruptions in distribution centers and disruptions between manufacturing centers and distribution centers. Meanwhile, it also focuses on the simultaneous disruption on one node or a number of nodes, simultaneous disruption in one chain or a number of chains and the corresponding mathematical models and exemplification in relation to numerous manufacturing centers and diverse products. Robustness of the design of the supply chain network is examined by weighing efficiency against robustness during supply chain disruptions. Efficiency is represented by operating cost; robustness is indicated by the expected disruption cost and the weighing issue is calculated by the multi-objective firefly algorithm for consistency in the results. It has been shown that the total cost achieved by the optimal target function is lower than that at the most effective time of supply chains. In other words, the decrease of expected disruption cost by improving robustness in supply chains is greater than the increase of operating cost by reducing efficiency, thus leading to cost advantage. Consequently, by approximating the Pareto Front Chart of weighing between efficiency and robustness, enterprises can choose appropriate efficiency and robustness for their longer-term development.

Suggested Citation

  • Tong Shu & Xiaoqin Gao & Shou Chen & Shouyang Wang & Kin Keung Lai & Lu Gan, 2016. "Weighing Efficiency-Robustness in Supply Chain Disruption by Multi-Objective Firefly Algorithm," Sustainability, MDPI, vol. 8(3), pages 1-27, March.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:3:p:250-:d:65341
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    References listed on IDEAS

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    2. Sinha, Priyank & Kumar, Sameer & Prakash, Surya, 2020. "Measuring and mitigating the effects of cost disturbance propagation in multi-echelon apparel supply chains," European Journal of Operational Research, Elsevier, vol. 282(1), pages 148-160.
    3. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    4. Jiguang Wang & Yucai Wu, 2018. "An Improved Voronoi-Diagram-Based Algorithm for Continuous Facility Location Problem under Disruptions," Sustainability, MDPI, vol. 10(9), pages 1-13, August.

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