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Shortest path with acceleration constraints: complexity and approximation algorithms

Author

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  • S. Ardizzoni

    (Università degli Studi di Parma)

  • L. Consolini

    (Università degli Studi di Parma)

  • M. Laurini

    (Università degli Studi di Parma)

  • M. Locatelli

    (Università degli Studi di Parma)

Abstract

We introduce a variant of the Shortest Path Problem (SPP), in which we impose additional constraints on the acceleration over the arcs, and call it Bounded Acceleration SPP (BASP). This variant is inspired by an industrial application: a vehicle needs to travel from its current position to a target one in minimum-time, following pre-defined geometric paths connecting positions within a facility, while satisfying some speed and acceleration constraints depending on the vehicle position along the currently traveled path. We characterize the complexity of BASP, proving its NP-hardness. We also show that, under additional hypotheses on problem data, the problem admits a pseudo-polynomial time-complexity algorithm. Moreover, we present an approximation algorithm with polynomial time-complexity with respect to the data of the original problem and the inverse of the approximation factor $$\epsilon$$ ϵ . Finally, we present some computational experiments to evaluate the performance of the proposed approximation algorithm.

Suggested Citation

  • S. Ardizzoni & L. Consolini & M. Laurini & M. Locatelli, 2022. "Shortest path with acceleration constraints: complexity and approximation algorithms," Computational Optimization and Applications, Springer, vol. 83(2), pages 555-592, November.
  • Handle: RePEc:spr:coopap:v:83:y:2022:i:2:d:10.1007_s10589-022-00403-w
    DOI: 10.1007/s10589-022-00403-w
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    References listed on IDEAS

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    1. Desrochers, Martin & Soumis, Francois, 1988. "A reoptimization algorithm for the shortest path problem with time windows," European Journal of Operational Research, Elsevier, vol. 35(2), pages 242-254, May.
    2. Villeneuve, Daniel & Desaulniers, Guy, 2005. "The shortest path problem with forbidden paths," European Journal of Operational Research, Elsevier, vol. 165(1), pages 97-107, August.
    3. Maurice Pollack, 1960. "Letter to the Editor---The Maximum Capacity Through a Network," Operations Research, INFORMS, vol. 8(5), pages 733-736, October.
    4. Stuart E. Dreyfus, 1969. "An Appraisal of Some Shortest-Path Algorithms," Operations Research, INFORMS, vol. 17(3), pages 395-412, June.
    5. Stefan Irnich & Guy Desaulniers, 2005. "Shortest Path Problems with Resource Constraints," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 33-65, Springer.
    6. 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).
    7. Moshe Dror, 1994. "Note on the Complexity of the Shortest Path Models for Column Generation in VRPTW," Operations Research, INFORMS, vol. 42(5), pages 977-978, October.
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