Paper Info
Title
Solving a new variant of the capacitated maximal covering location problem with fuzzy coverage area using metaheuristic approaches
Abstract
The Maximal Covering Location Problem (MCLP) is concerned with the optimal placement of a fixed number of facilities to cover the maximum number of customers. This article considers a new variant of MCLP where both the coverage radii of facilities and the distance between customer and facility are fuzzy. Moreover, the finite capacity of each facility is considered. We call this problem the capacitated MCLP with fuzzy coverage area (FCMCLP), and it is formulated as a 0–1 linear programming problem. In this article, two classical metaheuristics: particle swarm optimization, differential evolution, and two new-generation metaheuristics: artificial bee colony algorithm, firefly algorithm, are proposed for solving FCMCLP. Each of the customized metaheuristics utilizes a greedy deterministic heuristic to generate their initial populations. They also incorporate a local neighborhood search to improve their convergence rates. New instances of FCMCLP are generated from the traditional MCLP instances available in the literature, and IBM’s CPLEX solver is used to generate benchmark solutions. An experimental comparative study among the four customized metaheuristics is described in this article. The performances of the proposed metaheuristics are also compared with the benchmark solutions obtained from CPLEX.
Year
DOI
Venue
2022
10.1016/j.cie.2022.108315
Computers & Industrial Engineering
Keywords
DocType
Volume
Facility Location Problem (FLP),Fuzzy Capacitated Maximal Covering Location Problem (FCMCLP),Particle Swarm Optimization (PSO),Differential Evolution (DE),Artificial Bee Colony (ABC),Firefly Algorithm (FA)
Journal
170
ISSN
Citations 
PageRank 
0360-8352
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Soumen Atta100.34
Priya Ranjan Sinha Mahapatra200.34
Anirban Mukhopadhyay371150.07