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A stochastic look-ahead approach for hurricane relief logistics operations planning under uncertainty

Author

Listed:
  • Yanbin Chang

    (Clemson University)

  • Yongjia Song

    (Clemson University)

  • Burak Eksioglu

    (University of Arkansas)

Abstract

In the aftermath of a hurricane, humanitarian logistics plays a critical role in delivering relief items to the affected areas in a timely fashion. This paper proposes a novel stochastic look-ahead framework that implements a two-stage stochastic programming model in a rolling horizon approach to address the evolving uncertain logistics system state during the post-hurricane humanitarian logistics operations. The two-stage stochastic programming model that executes in this rolling horizon approach is formulated as a mixed-integer programming problem. The model aims to minimize the total cost incurred in the logistics operations, which consist of transportation cost and social cost. The social cost is measured as a function of deprivation for unsatisfied demand. Our extensive numerical results and sensitivity analysis demonstrate the effectiveness of the proposed approach in reducing the total cost incurred during the post-hurricane relief logistics operations compared to the two-stage stochastic programming model implemented in a static fashion.

Suggested Citation

  • Yanbin Chang & Yongjia Song & Burak Eksioglu, 2022. "A stochastic look-ahead approach for hurricane relief logistics operations planning under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 1231-1263, December.
  • Handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-021-04025-z
    DOI: 10.1007/s10479-021-04025-z
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