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

Yanbin Chang (), Yongjia Song () and Burak Eksioglu ()
Additional contact information
Yanbin Chang: Clemson University
Yongjia Song: Clemson University
Burak Eksioglu: University of Arkansas

Annals of Operations Research, 2022, vol. 319, issue 1, No 37, 1263 pages

Abstract: 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.

Keywords: Stochastic programming; Rolling horizon; Disaster relief logistics; Social cost (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-021-04025-z

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