Abstract
We consider the general multi-vehicle and multi-period Inventory Routing Problem (IRP). A challenging aspect of solving IRPs is how to capture the relationship among the periods where the routing takes place. Once the routes are defined, computing the optimal inventory at each customer on each period amounts to solving a network flow problem. We investigate the impact of efficiently solving this recurring network problem on the solutions found by the devised algorithm. A very significant impact is observed when solving 638 instances in a classical benchmark set, improving 113 upper bounds through assembling the network optimization into an ILS-RVND algorithm. In particular, the results suggested this approach performs better for larger instances with more periods, obtaining speed-ups of about ten times. A detailed comparison against nine of the most prominent exact and heuristic methods favors the proposed approach.
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Acknowledgements
This research was partially supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), grants 140084/2017-7, 313521/2017-4, 425962/2016-4 and 311954/2017-0, and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES), Financing Code 001. All support is gratefully acknowledged.
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Diniz, P., Martinelli, R., Poggi, M. (2020). An Efficient Matheuristic for the Inventory Routing Problem. In: Baïou, M., Gendron, B., Günlük, O., Mahjoub, A.R. (eds) Combinatorial Optimization. ISCO 2020. Lecture Notes in Computer Science(), vol 12176. Springer, Cham. https://doi.org/10.1007/978-3-030-53262-8_23
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