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An enhanced K-SP algorithm with pruning strategies to solve the constrained shortest path problem

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  • Sedeño-Noda, Antonio
  • Alonso-Rodríguez, Sergio

Abstract

We propose an exact method to solve the constrained shortest path (CSP) problem. The new approach takes advantage of the binary partition strategy of a recent K shortest paths (K-SP) algorithm that allows posing numerous additional path constraints in the model without extra difficulty. We adapt and incorporate several pruning strategies from the literature on the CSP problem in this scheme and obtain a robust and scalable algorithm. The method is compared with the current best algorithm to solve the CSP problem and produces significant speedups in a wide range of network configurations. An example is given where the CSP problem is solved in road networks containing a million nodes and arcs.

Suggested Citation

  • Sedeño-Noda, Antonio & Alonso-Rodríguez, Sergio, 2015. "An enhanced K-SP algorithm with pruning strategies to solve the constrained shortest path problem," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 602-618.
    • Handle: RePEc:eee:apmaco:v:265:y:2015:i:c:p:602-618
    DOI: 10.1016/j.amc.2015.05.109
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    References listed on IDEAS

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    1. Pascoal, Marta M.B. & Sedeño-Noda, Antonio, 2012. "Enumerating K best paths in length order in DAGs," European Journal of Operational Research, Elsevier, vol. 221(2), pages 308-316.
    2. D. Klingman & A. Napier & J. Stutz, 1974. "NETGEN: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Network Problems," Management Science, INFORMS, vol. 20(5), pages 814-821, January.
    3. Luigi Di Puglia Pugliese & Francesca Guerriero, 2013. "A Reference Point Approach for the Resource Constrained Shortest Path Problems," Transportation Science, INFORMS, vol. 47(2), pages 247-265, May.
    4. Santos, Luis & Coutinho-Rodrigues, João & Current, John R., 2007. "An improved solution algorithm for the constrained shortest path problem," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 756-771, August.
    5. Namorado Climaco, Joao Carlos & Queiros Vieira Martins, Ernesto, 1982. "A bicriterion shortest path algorithm," European Journal of Operational Research, Elsevier, vol. 11(4), pages 399-404, December.
    6. Refael Hassin, 1992. "Approximation Schemes for the Restricted Shortest Path Problem," Mathematics of Operations Research, INFORMS, vol. 17(1), pages 36-42, February.
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