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A Reference Point Approach for the Resource Constrained Shortest Path Problems

Author

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  • Luigi Di Puglia Pugliese

    (Department of Electronics, Computer Science and Systems, University of Calabria, Rende (CS), Italy)

  • Francesca Guerriero

    (Department of Electronics, Computer Science and Systems, University of Calabria, Rende (CS), Italy)

Abstract

The Resource Constrained Shortest Path Problem ((R-script) (C-script) (S-script) (P-script) (P-script)) is a variant of the classical shortest path problem and is of great practical importance. The aim is to find the shortest path between a given pair of nodes under additional constraints representing upper bounds on the consumption of resources along the path. In the scientific literature, different approaches have been defined to solve the (R-script) (C-script) (S-script) (P-script) (P-script). In this work we propose an innovative interactive method to address the (R-script) (C-script) (S-script) (P-script) (P-script), based on a novel search strategy of the criteria space. The performance of the proposed approach is evaluated on the basis of an extensive computational study by considering benchmark instances. A comparison with the state-of-the-art approaches developed for the (R-script) (C-script) (S-script) (P-script) (P-script) is also carried out. The computational results have shown that the developed solution strategy is competitive with the most efficient strategies known thus far.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ortrsc:v:47:y:2013:i:2:p:247-265
    DOI: 10.1287/trsc.1120.0418
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    3. Trivella, Alessio & Corman, Francesco & Koza, David F. & Pisinger, David, 2021. "The multi-commodity network flow problem with soft transit time constraints: Application to liner shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
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    5. Chen, Bi Yu & Chen, Xiao-Wei & Chen, Hui-Ping & Lam, William H.K., 2020. "Efficient algorithm for finding k shortest paths based on re-optimization technique," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    6. 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.
    7. Luigi Di Puglia Pugliese & Francesca Guerriero, 2016. "On the shortest path problem with negative cost cycles," Computational Optimization and Applications, Springer, vol. 63(2), pages 559-583, March.
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    10. Antonio Frangioni & Laura Galli & Maria Grazia Scutellà, 2015. "Delay-Constrained Shortest Paths: Approximation Algorithms and Second-Order Cone Models," Journal of Optimization Theory and Applications, Springer, vol. 164(3), pages 1051-1077, March.

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