The multivehicle covering tour problem ( m ‐CTP) is a transportation problem with different kinds of locations, where a set of locations must be visited while another set must be close enough to planned routes. Given two sets of vertices V and W , where V represents the set of vertices that may be visited and W is a set of vertices that must be covered by up to m vehicles, the m ‐CTP problem is to minimize vehicle routes on a subset of V including T , which represents the subset of vertices that must be visited through the use of potential locations in V . The variant of m ‐CTP without a route‐length constraint is treated in this paper. To tackle this problem, we propose a variable neighborhood search heuristic based on variable neighborhood descent method. Experiments were conducted using the datasets based on traveling salesman problem library instances.
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Kammoun et al. (2016) studied this question.
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