000168062 001__ 168062
000168062 005__ 20260127151100.0
000168062 0247_ $$2doi$$a10.1016/j.cor.2020.105066
000168062 0248_ $$2sideral$$a119848
000168062 037__ $$aART-2020-119848
000168062 041__ $$aeng
000168062 100__ $$0(orcid)0000-0001-7603-9380$$aCalvete, H.I.$$uUniversidad de Zaragoza
000168062 245__ $$aA matheuristic for solving the bilevel approach of the facility location problem with cardinality constraints and preferences
000168062 260__ $$c2020
000168062 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168062 5203_ $$aThis paper addresses a generalized version of the facility location problem with customer preferences which includes an additional constraint on the number of customers which can be allocated to each facility. The model aims to minimize the total cost due to opening facilities and allocating customers while taking into account both customer preferences for the facilities and these cardinality constraints. First, two approaches to deal with this problem are proposed, which extend the single level and bilevel formulations of the problem in which customers are free to select their most preferred open facility. After analyzing the implications of assuming any of the two approaches, in this research, we adopt the approach based on the hierarchical character of the model which leads to the formulation of a bilevel optimization problem. Then, taking advantage of the characteristics of the lower level problem, a single level reformulation of the bilevel optimization model is developed based on duality theory which does not require the inclusion of additional binary variables. Finally, we develop a simple but effective matheuristic for solving the bilevel optimization problem whose general framework follows that of an evolutionary algorithm and exploits the bilevel structure of the model. The chromosome encoding pays attention to the upper level variables and controls the facilities which are open. Then, an optimization model is solved to allocate customers in accordance with their preferences and the availability of the open facilities. A computational experiment shows the effectiveness of the matheuristic in terms of the quality of the solutions yielded and the computing time.
000168062 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E41-17R$$9info:eu-repo/grantAgreement/ES/MINECO/ECO2013-47129-C4-3-R$$9info:eu-repo/grantAgreement/ES/MINECO/ECO2016-76567-C4-3-R
000168062 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000168062 590__ $$a4.008$$b2020
000168062 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b39 / 111 = 0.351$$c2020$$dQ2$$eT2
000168062 591__ $$aOPERATIONS RESEARCH & MANAGEMENT SCIENCE$$b25 / 84 = 0.298$$c2020$$dQ2$$eT1
000168062 591__ $$aENGINEERING, INDUSTRIAL$$b17 / 49 = 0.347$$c2020$$dQ2$$eT2
000168062 592__ $$a1.506$$b2020
000168062 593__ $$aComputer Science (miscellaneous)$$c2020$$dQ1
000168062 593__ $$aModeling and Simulation$$c2020$$dQ1
000168062 593__ $$aManagement Science and Operations Research$$c2020$$dQ1
000168062 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000168062 700__ $$0(orcid)0000-0002-5630-3719$$aGalé, C.$$uUniversidad de Zaragoza
000168062 700__ $$0(orcid)0000-0001-9993-9816$$aIranzo, J.A.$$uUniversidad de Zaragoza
000168062 700__ $$aCamacho-Vallejo, J.F.
000168062 700__ $$aCasas-Ramírez, M.S.
000168062 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000168062 773__ $$g124 (2020), 105066 [15 pp.]$$pComput. oper. res.$$tComputers and Operations Research$$x0305-0548
000168062 8564_ $$s622496$$uhttps://zaguan.unizar.es/record/168062/files/texto_completo.pdf$$yPostprint
000168062 8564_ $$s1950794$$uhttps://zaguan.unizar.es/record/168062/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000168062 909CO $$ooai:zaguan.unizar.es:168062$$particulos$$pdriver
000168062 951__ $$a2026-01-27-15:07:22
000168062 980__ $$aARTICLE