Joint inventory-location problem under the risk of probabilistic facility disruptions

Qi Chen, Xiaopeng Li, Yanfeng Ouyang

Research output: Contribution to journalArticlepeer-review


This paper studies a reliable joint inventory-location problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks (e.g., due to natural or man-made hazards). When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. We propose an integer programming model that minimizes the sum of facility construction costs, expected inventory holding costs and expected customer costs under normal and failure scenarios. We develop a Lagrangian relaxation solution framework for this problem, including a polynomial-time exact algorithm for the relaxed nonlinear subproblems. Numerical experiment results show that this proposed model is capable of providing a near-optimum solution within a short computation time. Managerial insights on the optimal facility deployment, inventory control strategies, and the corresponding cost constitutions are drawn.

Original languageEnglish (US)
Pages (from-to)991-1003
Number of pages13
JournalTransportation Research Part B: Methodological
Issue number7
StatePublished - Aug 2011


  • Disruption
  • Facility location
  • Joint inventory-location problem
  • Lagrangian relaxation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation


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