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Supply chain downsizing under bankruptcy: A robust optimization approach

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  • Ashayeri, J.
  • Ma, N.
  • Sotirov, R.

Abstract

Research on supply chain network design has mainly pursued efficiency oriented objectives for boosting service level and profit. However, the priority of an enterprise facing bankruptcy pressure shifts to fulfill debt obligation with limited financial resources and survive downsizing. In this paper, we define a supply chain downsizing problem (SCDP) under bankruptcy as streamlining a supply chain network in order to balance a business survival and its long term profitability. We formulate a mixed integer programming (MIP) model with specific downsizing features, which maximizes the utilization of investment resources through a combined operation of demand selection and production assets reallocation. The corresponding robust counterparts of the MIP model are further developed based on robust optimization techniques for dealing with uncertainties of demands and exchange rates. We analyze and validate the proposed downsizing MIP model with a series of systematically generated test cases while its robust counterparts are studied extensively using a large generated case. The findings demonstrate the value of our approach in discovering detailed downsizing plans in magnitude and direction and provide valuable insight into how financial debt payback could be arranged, and in a unique way show managers how the reconfigured downsized network would mitigate and lead to a sustainable and higher economic value supply chain.

Suggested Citation

  • Ashayeri, J. & Ma, N. & Sotirov, R., 2014. "Supply chain downsizing under bankruptcy: A robust optimization approach," International Journal of Production Economics, Elsevier, vol. 154(C), pages 1-15.
  • Handle: RePEc:eee:proeco:v:154:y:2014:i:c:p:1-15
    DOI: 10.1016/j.ijpe.2014.04.004
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    Cited by:

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    2. Hou, Yunzhang & Wang, Xiaoling & Wu, Yenchun Jim & He, Peixu, 2018. "How does the trust affect the topology of supply chain network and its resilience? An agent-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 229-241.
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