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Shortest path interdiction problem with arc improvement recourse: A multiobjective approach

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  • Tim Holzmann
  • J. Cole Smith

Abstract

We consider the shortest path interdiction problem involving two agents, a leader and a follower, playing a Stackelberg game. The leader seeks to maximize the follower's minimum costs by interdicting certain arcs, thus increasing the travel time of those arcs. The follower may improve the network after the interdiction by lowering the costs of some arcs, subject to a cardinality budget restriction on arc improvements. The leader and the follower are both aware of all problem data, with the exception that the leader is unaware of the follower's improvement budget. The effectiveness of an interdiction action is given by the length of a shortest path after arc costs are adjusted by both the interdiction and improvement. We propose a multiobjective optimization model for this problem, with each objective corresponding to a different possible improvement budget value. We provide mathematical optimization techniques to generate a complete set of strategies that are Pareto‐optimal. Additionally, for the special case of series‐parallel graphs, we provide a dynamic‐programming algorithm for generating all Pareto‐optimal solutions.

Suggested Citation

  • Tim Holzmann & J. Cole Smith, 2019. "Shortest path interdiction problem with arc improvement recourse: A multiobjective approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(3), pages 230-252, April.
  • Handle: RePEc:wly:navres:v:66:y:2019:i:3:p:230-252
    DOI: 10.1002/nav.21839
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    References listed on IDEAS

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    1. Patrice Perny & Olivier Spanjaard & Louis-Xavier Storme, 2006. "A decision-theoretic approach to robust optimization in multivalued graphs," Annals of Operations Research, Springer, vol. 147(1), pages 317-341, October.
    2. Clyde L. Monma & Jeffrey B. Sidney, 1979. "Sequencing with Series-Parallel Precedence Constraints," Mathematics of Operations Research, INFORMS, vol. 4(3), pages 215-224, August.
    3. Brian Lunday & Hanif Sherali, 2012. "Network interdiction to minimize the maximum probability of evasion with synergy between applied resources," Annals of Operations Research, Springer, vol. 196(1), pages 411-442, July.
    4. Hites, R. & De Smet, Y. & Risse, N. & Salazar-Neumann, M. & Vincke, P., 2006. "About the applicability of MCDA to some robustness problems," European Journal of Operational Research, Elsevier, vol. 174(1), pages 322-332, October.
    5. Dächert, Kerstin & Klamroth, Kathrin & Lacour, Renaud & Vanderpooten, Daniel, 2017. "Efficient computation of the search region in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 260(3), pages 841-855.
    6. Leonardo Lozano & J. Cole Smith, 2017. "A Backward Sampling Framework for Interdiction Problems with Fortification," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 123-139, February.
    7. Dan A. Iancu & Nikolaos Trichakis, 2014. "Pareto Efficiency in Robust Optimization," Management Science, INFORMS, vol. 60(1), pages 130-147, January.
    8. Thomas Stidsen & Kim Allan Andersen & Bernd Dammann, 2014. "A Branch and Bound Algorithm for a Class of Biobjective Mixed Integer Programs," Management Science, INFORMS, vol. 60(4), pages 1009-1032, April.
    9. Klein, Dieter & Hannan, Edward, 1982. "An algorithm for the multiple objective integer linear programming problem," European Journal of Operational Research, Elsevier, vol. 9(4), pages 378-385, April.
    10. Holzmann, Tim & Smith, J.C., 2018. "Solving discrete multi-objective optimization problems using modified augmented weighted Tchebychev scalarizations," European Journal of Operational Research, Elsevier, vol. 271(2), pages 436-449.
    11. Konrad, Renata A. & Trapp, Andrew C. & Palmbach, Timothy M. & Blom, Jeffrey S., 2017. "Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications," European Journal of Operational Research, Elsevier, vol. 259(2), pages 733-745.
    12. Klamroth, Kathrin & Köbis, Elisabeth & Schöbel, Anita & Tammer, Christiane, 2017. "A unified approach to uncertain optimization," European Journal of Operational Research, Elsevier, vol. 260(2), pages 403-420.
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    Cited by:

    1. Kosmas, Daniel & Sharkey, Thomas C. & Mitchell, John E. & Maass, Kayse Lee & Martin, Lauren, 2023. "Interdicting restructuring networks with applications in illicit trafficking," European Journal of Operational Research, Elsevier, vol. 308(2), pages 832-851.

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