an efficient genetic algorithm for the uncapacitated r-allocation p-hub maximal covering problem
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ID: 128787
2018
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Abstract
This paper deals with the Uncapacitated r-allocation p-hub Maximal Covering Problem (UrApHMCP) with a binary coverage criterion. This problem consists of choosing p hub locations from a set of nodes so as to maximize the total demand covered under the r-allocation strategy. The general assumption is that the transportation between the nonhub nodes is possible only via hub nodes, while each non-hub node is assigned to at most r hubs. An integer linear programming formulation of the UrApHMCP is presented and tested within the framework of a commercial CPLEX solver. In order to solve the problem on large scale hub instances that cannot be handled by the CPLEX, a Genetic Algorithm (GA) is proposed. The results of computational experiments on standard p-hub benchmark instances with up to 200 nodes demonstrate efficiency and effectiveness of the proposed GA method.
| Reference Key |
olivera2018yugoslavan
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|---|---|
| Authors | ;Janković Olivera |
| Journal | chemnanomat |
| Year | 2018 |
| DOI |
10.2298/YJOR170120011J
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| URL | |
| Keywords | Keywords not found |
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