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An Iterated Local Search for the Budget Constrained Generalized Maximal Covering Location Problem

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Journal of Mathematical Modelling and Algorithms in Operations Research

Abstract

Capacitated covering models aim at covering the maximum amount of customers’ demand using a set of capacitated facilities. Based on the assumptions made in such models, there is a unique scenario to open a facility in which each facility has a pre-specified capacity and an operating budget. In this paper, we propose a generalization of the maximal covering location problem, in which facilities have different scenarios for being constructed. Essentially, based on the budget invested to construct a given facility, it can provide different service levels to the surrounded customers. Having a limited budget to open the facilities, the goal is locating a subset of facilities with the optimal opening scenario, in order to maximize the total covered demand and subject to the service level constraint. Integer linear programming formulations are proposed and tested using ILOG CPLEX. An iterated local search algorithm is also developed to solve the introduced problem.

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  1. Department of Industrial Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Majid Salari

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  1. Majid Salari
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Salari, M. An Iterated Local Search for the Budget Constrained Generalized Maximal Covering Location Problem. J Math Model Algor 13, 301–313 (2014). https://doi.org/10.1007/s10852-013-9233-9

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  • DOI: https://doi.org/10.1007/s10852-013-9233-9

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