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

Authors :
Chang, Yanbin
Song, Yongjia
Eksioglu, Burak
Source :
Annals of Operations Research. Dec2022, Vol. 319 Issue 1, p1231-1263. 33p.
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02545330
Volume :
319
Issue :
1
Database :
Academic Search Index
Journal :
Annals of Operations Research
Publication Type :
Academic Journal
Accession number :
160764416
Full Text :
https://doi.org/10.1007/s10479-021-04025-z