Abstract
Heuristics for stochastic and dynamic vehicle routing problems are often kept relatively simple, in part due to the high computational burden resulting from having to consider stochastic information in some form. In this work, three existing heuristics are extended by three different local search variations: a first improvement descent using stochastic information, a tabu search using stochastic information when updating the incumbent solution, and a tabu search using stochastic information when selecting moves based on a list of moves determined through a proxy evaluation. In particular, the three local search variations are designed to utilize stochastic information in the form of sampled scenarios. The results indicate that adding local search using stochastic information to the existing heuristics can further reduce operating costs for shipping companies by 0.5–2 %. While the existing heuristics could produce structurally different solutions even when using similar stochastic information in the search, the appended local search methods seem able to make the final solutions more similar in structure.
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Acknowledgments
This research was carried out with financial support from the DOMinant II Project, partly funded by the Research Council of Norway, from a Grant from Iceland, Liechtenstein and Norway through the EEA Financial Mechanism (operated by Universidad Complutense de Madrid) with reference 026-ABELIM-2013, and from the Government of Spain, Grant TIN2012-32482. The authors are grateful for the inputs from three anonymous reviewers.
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Tirado, G., Hvattum, L.M. Improved solutions to dynamic and stochastic maritime pick-up and delivery problems using local search. Ann Oper Res 253, 825–843 (2017). https://doi.org/10.1007/s10479-016-2177-5
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DOI: https://doi.org/10.1007/s10479-016-2177-5