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A hybrid Tabu search – variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications

Kyriakakis Nikolaos-Antonios, Sevastopoulos Ioanni, Marinaki Magdalini, Marinakis Ioannis

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URI: http://purl.tuc.gr/dl/dias/F5CBEA79-58D3-45E2-96DA-E1C8062331FD
Year 2022
Type of Item Peer-Reviewed Journal Publication
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Bibliographic Citation N. A. Kyriakakis, I. Sevastopoulos, M. Marinaki, and Y. Marinakis, “A hybrid Tabu search – variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications,” Comput. Ind. Eng., vol. 164, Feb. 2022, doi: 10.1016/j.cie.2021.107868. https://doi.org/10.1016/j.cie.2021.107868
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Summary

The paper presents a Hybrid Tabu Search - Variable Neighborhood Descent (HTS-VND) metaheuristic algorithm for the Cumulative Capacitated Vehicle Routing Problem with Time Windows (CCVRPTW). The algorithm is also used to solve the Cumulative Capacitated Vehicle Routing Problem (CCVRP) without the time widow constraints. Its effectiveness is tested against well known benchmark instances from the literature and the results are compared with the results of other state-of-the-art approaches. The proposed metaheuristic was able to find new best known solutions in two instances of the CCVRP. For the CCVRPTW, two additional algorithms, a Tabu Search algorithm and a Variable Neighborhood Descent algorithm, were implemented to provide benchmark values for results obtained with HTS-VND. Overall, on the 92 CCVRP instances tested, the best known solutions were reached in 84 of them. For the CCVRPTW, 56 instances were tested and the proposed HTS-VND obtained better results than the two pure implementations, reaching the instance specified number of vehicles in 41 of them. The paper also provides solution cost values for the CCVRPTW, which are not included in approaches in the literature.

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