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@Article{PereiraCoelLoreSouz:2015:HyMePr,
               author = "Pereira, Marcos A. and Coelho, Leandro C. and Lorena, Luiz Antonio 
                         Nogueira and Souza, Ligia C. de",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and Interuniversity 
                         Research Centre on Enterprise Network, Logistics and 
                         Transportation (CIRRELT) and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "A hybrid method for the probabilistic maximal covering location 
                         allocation problem",
              journal = "Computers and Operations Research",
                 year = "2015",
               volume = "57",
                pages = "51--59",
                month = "May",
             keywords = "adaptive large neighborhood search, congested systems, exact 
                         method, facility location, hybrid algorithm, PMCLAP, queueing 
                         maximal covering location-allocation model.",
             abstract = "This paper presents a hybrid algorithm that combines a 
                         metaheuristic and an exact method to solve the Probabilistic 
                         Maximal Covering Location-Allocation Problem. A linear programming 
                         formulation for the problem presents variables that can be 
                         partitioned into location and allocation decisions. This model is 
                         solved to optimality for small- and medium-size instances. To 
                         tackle larger instances, a flexible adaptive large neighborhood 
                         search heuristic was developed to obtain location solutions, 
                         whereas the allocation subproblems are solved to optimality. An 
                         improvement procedure based on an integer programming method is 
                         also applied. Extensive computational experiments on benchmark 
                         instances from the literature confirm the efficiency of the 
                         proposed method. The exact approach found new best solutions for 
                         19 instances, proving the optimality for 18 of them. The hybrid 
                         method performed consistently, finding the best known solutions 
                         for 94.5% of the instances and 17 new best solutions (15 of them 
                         optimal) for a larger dataset in one-third of the time of a 
                         state-of-the-art solver.",
                  doi = "10.1016/j.cor.2014.12.001",
                  url = "http://dx.doi.org/10.1016/j.cor.2014.12.001",
                 issn = "0305-0548",
             language = "en",
        urlaccessdate = "24 nov. 2020"
}


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