4.5 Article

A two-stage stochastic programming model for transportation network protection

期刊

COMPUTERS & OPERATIONS RESEARCH
卷 36, 期 5, 页码 1582-1590

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2008.03.001

关键词

Stochastic programming; Network design; Generalized Benders decomposition; L-shaped; Critical infrastructure protection; Disaster mitigation

资金

  1. National Science Foundation
  2. California Department of Transportation
  3. Pacific Earthquake Engineering (PEER) research center

向作者/读者索取更多资源

Network protection against natural and human-caused hazards has become a topical research theme in engineering and social sciences. This paper focuses on the problem of allocating limited retrofit resources over multiple highway bridges to improve the resilience and robustness of the entire transportation system in question. The main modeling challenges in network retrofit problems are to capture the interdependencies among individual transportation facilities and to cope with the extremely high uncertainty in the decision environment. In this paper, we model the network retrofit problem as a two-stage stochastic programming problem that optimizes a mean-risk objective of the system loss. This formulation hedges well against uncertainty, but also imposes computational challenges due to involvement of integer decision variables and increased dimension of the problem. An efficient algorithm is developed, via extending the well-known L-shaped method using generalized benders decomposition, to efficiently handle the binary integer variables in the first stage and the nonlinear recourse in the second stage of the model formulation. The proposed modeling and solution methods are general and can be applied to other network design problems as well. (c) 2008 Elsevier Ltd. All rights reserved.

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