Networks and Spatial Economics

, Volume 10, Issue 2, pp 193–208 | Cite as

Solving Stochastic Transportation Network Protection Problems Using the Progressive Hedging-based Method

Article
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Abstract

This research focuses on pre-disaster transportation network protection against uncertain future disasters. Given limited resources, the goal of the central planner is to choose the best set of network components to protect while allowing the network users to follow their own best-perceived routes in any resultant network configuration. This problem is formulated as a two-stage stochastic programming problem with equilibrium constraints, where the objective is to minimize the total expected physical and social losses caused by potential disasters. Developing efficient solution methods for such a problem can be challenging. In this work, we will demonstrate the applicability of progressive hedging-based method for solving large scale stochastic network optimization problems with equilibrium constraints. In the proposed solution procedure, we solve each modified scenario sub-problem as a mathematical program with complementary constraints and then gradually aggregate scenario-dependent solutions to the final optimal solution.

Keywords

Stochastic programming Networks Disaster mitigation Equilibrium constraints Decomposition method 
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Notes

Acknowledgments

The authors would like to thank National Science Foundation and California Department of Transportation for supporting this research through the Pacific Earthquake Engineering research center. Helpful discussions with Prof. Roger Wets and Prof. David Woodruff at University of California, Davis, and Dr. Jeff Ban at University of California, Berkeley, CA, USA are gratefully acknowledged.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Department of Civil and Environmental Engineering and Institute of Transportation StudiesUniversity of CaliforniaDavisUSA

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