Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/8548
Title: An efficient genetic algorithm for the uncapacitated R-allocation P-hub maximal covering problem
Authors: Jankovic, Olivera
Issue Date: 2018
Abstract: © 2018 Faculty of Organizational Sciences, Belgrade. All Rights Reserved. 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 non-hub 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.
URI: https://scidar.kg.ac.rs/handle/123456789/8548
Type: article
DOI: 10.2298/YJOR170120011J
ISSN: 0354-0243
SCOPUS: 2-s2.0-85049148283
Appears in Collections:Faculty of Economics, Kragujevac

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