The complete vertex p-center problem

dc.contributor.authorMedrano, Fernando Antonio
dc.date.accessioned2022-02-02T18:02:21Z
dc.date.available2022-02-02T18:02:21Z
dc.date.issued2020-08-05
dc.description.abstractThe vertex p-center problem consists of locating p facilities among a set of M potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex p-center problem solves the p-center problem for all p from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This trade-off provides a reference to planners and decision makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. We present two fast algorithms for solving the complete p-center problem: one using the classical formulation but trimming variables while still maintaining optimality and the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. We also discuss scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speedups, with the set covering method reducing computation times by many orders of magnitude.en_US
dc.description.abstractThe vertex p-center problem consists of locating p facilities among a set of M potential sites such that the maximum distance from any demand to its closest located facility is minimized. The complete vertex p-center problem solves the p-center problem for all p from 1 to the total number of sites, resulting in a multi-objective trade-off curve between the number of facilities and the service distance required to achieve full coverage. This trade-off provides a reference to planners and decision makers, enabling them to easily visualize the consequences of choosing different coverage design criteria for the given spatial configuration of the problem. We present two fast algorithms for solving the complete p-center problem: one using the classical formulation but trimming variables while still maintaining optimality and the other converting the problem to a location set covering problem and solving for all distances in the distance matrix. We also discuss scenarios where it makes sense to solve the problem via brute-force enumeration. All methods result in significant speedups, with the set covering method reducing computation times by many orders of magnitude.
dc.identifier.citationMedrano, F.A., 2020. The complete vertex p-center problem. EURO Journal on Computational Optimization, 8(3), pp.327-343.en_US
dc.identifier.citationMedrano, F.A., 2020. The complete vertex p-center problem. EURO Journal on Computational Optimization, 8(3), pp.327-343.
dc.identifier.doihttps://doi.org/10.1007/s13675-020-00131-y
dc.identifier.urihttps://hdl.handle.net/1969.6/90135
dc.language.isoen_USen_US
dc.language.isoen_US
dc.publisherSpringeren_US
dc.publisherSpringer
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectp-centeren_US
dc.subjectfacilityen_US
dc.subjectfacility locationen_US
dc.subjectlocation set coveringen_US
dc.subjectspatial optimizationen_US
dc.subjectlocation-allocationen_US
dc.subjectmathematical programmingen_US
dc.subjectp-center
dc.subjectfacility
dc.subjectfacility location
dc.subjectlocation set covering
dc.subjectspatial optimization
dc.subjectlocation-allocation
dc.subjectmathematical programming
dc.titleThe complete vertex p-center problemen_US
dc.titleThe complete vertex p-center problem
dc.typeArticleen_US
dc.typeArticle

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