期刊
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
卷 45, 期 8, 页码 1177-1189出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trb.2010.09.002
关键词
Robust optimization; Dynamic traffic assignment; Demand uncertainty; Emergency logistics
类别
资金
- National Science Foundation [CMMI-0824640, CMMI-0900040]
- Marcus - Technion/PSU Partnership Program
- Directorate For Engineering
- Div Of Civil, Mechanical, & Manufact Inn [0824640] Funding Source: National Science Foundation
This paper proposes a methodology to generate a robust logistics plan that can mitigate demand uncertainty in humanitarian relief supply chains. More specifically, we apply robust optimization (RO) for dynamically assigning emergency response and evacuation traffic flow problems with time dependent demand uncertainty. This paper studies a Cell Transmission Model (CTM) based system optimum dynamic traffic assignment model. We adopt a min-max criterion and apply an extension of the RO method adjusted to dynamic optimization problems, an affinely adjustable robust counterpart (AARC) approach. Simulation experiments show that the AARC solution provides excellent results when compared to deterministic solution and sampling based stochastic programming solution. General insights of RO and transportation that may have wider applicability in humanitarian relief supply chains are provided. (C) 2010 Elsevier Ltd. All rights reserved.
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