An Adaptive Large Neighborhood Search Heuristic for a Multi-Period Vehicle Routing Problem
نویسندگان
چکیده
We consider tactical planning for a particular class of multi-period vehicle routing problems (MPVRP). This problem involves optimizing product collection and distribution from several production locations to a set of processing plants over a planning horizon. Each horizon consists of several days, and the collection-distribution are performed on a repeating daily basis. In this context, a single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season, and intra-season variations are neglected. We propose an adaptive large neighborhood search with several special operators and features. To evaluate the performance of the algorithm we performed an extensive series of numerical tests. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.
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