期刊
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 282, 期 1, 页码 40-57出版社
ELSEVIER
DOI: 10.1016/j.ejor.2019.09.008
关键词
Humanitarian logistics; Needs assessment; Robust optimization; Routing; Travel time uncertainty
资金
- Scientific and Technologi-cal Research Council of Turkey Career Award [213M414]
We focus on rapid needs assessment operations conducted immediately after a disaster to identify the urgent needs of the affected community groups, and address the problem of selecting the sites to be visited by the assessment teams during a fixed assessment period and constructing assessment routes under travel time uncertainty. Due to significant uncertainties in post-disaster transportation network conditions, only rough information on travel times may be available during rapid needs assessment planning. We represent uncertain travel times simply by specifying a range of values, and implement robust optimization methods to ensure that each constructed route is feasible for all realizations of the uncertain parameters that lie in a predetermined uncertainty set. We present a tractable robust optimization formulation with a coaxial box uncertainty set due to its advantages in handling uncertainty in our selective assessment routing problem, in which the dimension of the uncertainty (number of arcs traversed) is implicitly determined. To solve the proposed model efficiently, we develop a practical method for evaluating route feasibility with respect to the robust route duration constraints, and embed this feasibility check procedure in a tabu search heuristic. We present computational results to evaluate the effectiveness of our solution method, and illustrate our approach on a case study based on a real-world post-disaster network. (C) 2019 Elsevier B.V. All rights reserved.
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