The multimode covering location problem

Colombo, Fabio and Cordone, Roberto and Lulli, Guglielmo (2016) The multimode covering location problem. Computers and Operations Research, 67. 25–33. ISSN 0305-0548

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In this paper we introduce the Multimode Covering Location Problem. This is a generalization of the Maximal Covering Location Problem that consists in locating a given number of facilities of different types with a limitation on the number of facilities sharing the same site. The problem is challenging and intrinsically much harder than its basic version. Nevertheless, it admits a constant factor approximation guarantee, which can be achieved combining two greedy algorithms. To improve the greedy solutions, we have developed a Variable Neighborhood Search approach, based on an exponential-size neighborhood. This algorithm computes good quality solutions in short computational time. The viability of the approach here proposed is also corroborated by a comparison with a Heuristic Concentration algorithm, which is presently the most effective approach to solve large instances of the Maximal Covering Location Problem.

Item Type:
Journal Article
Journal or Publication Title:
Computers and Operations Research
Additional Information:
This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 67, 2016 DOI: 10.1016/j.cor.2015.09.003
Uncontrolled Keywords:
?? maximal covering location problemvariable neighborhood searchvery large scale neighborhood searchheuristic concentrationmodelling and simulationmanagement science and operations researchgeneral computer sciencecomputer science(all)discipline-based researc ??
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Deposited On:
19 Feb 2016 09:52
Last Modified:
16 Jul 2024 09:56