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Acceleration strategies for the weight constrained shortest path problem with replenishment

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Abstract

The weight constrained shortest path problem with replenishment (WCSPP-R) generalizes the constrained shortest path problem (CSP) and has multiple applications in transportation, scheduling, and telecommunications. We present an exact algorithm based on a recursive depth-first search that combines and extends ideas proposed in state-of-the-art algorithms for the CSP and the WCSPP-R. The novelty lies in a set of acceleration strategies that significantly improves the algorithm’s performance. We conducted experiments over large real-road networks with up to 6 million nodes and 15 million arcs, achieving speedups of up to 219 times against the state-of-the-art algorithm.

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Authors and Affiliations

  1. Universidad de Los Andes, Cr 1E No. 19A-10, ML711, Bogotá, Colombia

    Manuel A. Bolívar, Leonardo Lozano & Andrés L. Medaglia

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  1. Manuel A. Bolívar
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  2. Leonardo Lozano
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  3. Andrés L. Medaglia
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Correspondence to Andrés L. Medaglia.

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Bolívar, M.A., Lozano, L. & Medaglia, A.L. Acceleration strategies for the weight constrained shortest path problem with replenishment. Optim Lett 8, 2155–2172 (2014). https://doi.org/10.1007/s11590-014-0742-x

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  • DOI: https://doi.org/10.1007/s11590-014-0742-x

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