BY-NC-NDJankovic, Olivera2020-09-192020-09-1920180354-0243https://scidar.kg.ac.rs/handle/123456789/8548© 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.openAccesshttps://creativecommons.org/licenses/by-nc-nd/4.0/An efficient genetic algorithm for the uncapacitated R-allocation P-hub maximal covering problemarticle10.2298/YJOR170120011J2-s2.0-85049148283