Supply chain downsizing under bankruptcy: A robust optimization approach

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)1-15
JournalInternational Journal of Production Economics
Volume154
Issue numberAugust 2014
Early online date18 Apr 2014
DOIs
Publication statusPublished - Aug 2014

Keywords

  • supply chain
  • downsizing
  • bankruptcy
  • robust optimization
  • uncertain demand
  • uncertain exchange rate

Fingerprint

Dive into the research topics of 'Supply chain downsizing under bankruptcy: A robust optimization approach'. Together they form a unique fingerprint.

Cite this