Abstract
In this paper, a multiobjective adaptive large neighborhood search is proposed for a vehicle routing problem (VRP) of which the objectives are the total travel time and the cumulative time, i.e., the total arrival time at all customers. It hybrids destroy-repair operators with local search for generating new solutions. An adaptive probabilistic rule based on Pareto dominance is proposed to select a combination of destroy-repair operator. The effectiveness of the proposed algorithm is supported by the experimental study.
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CITATION STYLE
Ke, L., & Zhai, L. (2014). A multiobjective large neighborhood search for a vehicle routing problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8795, pp. 301–308). Springer Verlag. https://doi.org/10.1007/978-3-319-11897-0_36
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