| Title: | Solving a new variant of the capacitated maximal covering location problem with fuzzy coverage area using metaheuristic approaches |
|---|
| Authors: | ID Atta, Soumen, Laboratoire des Sciences du Numérique de Nantes (LS2N), UMR 6004, UFR Sciences et Techniques, Université de Nantes, IMT Atlantique, 4 Rue Alfred Kastler, Nantes 44307, France (Author)
ID Sinha Mahapatra, Priya Ranjan, Department of Computer Science and Engineering, University of Kalyani, Kalyani, 741235, West Bengal, India (Author)
ID Mukhopadhyay, Anirban, Department of Computer Science and Engineering, University of Kalyani, Kalyani, 741235, West Bengal, India (Author) |
|---|
| Files: |
This document has no files that are freely available to the public. This document may have a physical copy in the library of the organization, check the status via COBISS.  |
|---|
| Language: | English |
|---|
| Work type: | Not categorized |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: | UNG - University of Nova Gorica
|
|---|
| 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. |
|---|
| Keywords: | 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) |
|---|
| Publication version: | Version of Record |
|---|
| Year of publishing: | 2022 |
|---|
| Number of pages: | 108315 |
|---|
| Numbering: | August, 170 |
|---|
| PID: | 20.500.12556/RUNG-8023 |
|---|
| COBISS.SI-ID: | 144448259 |
|---|
| DOI: | https://doi.org/10.1016/j.cie.2022.108315 |
|---|
| NUK URN: | URN:SI:UNG:REP:MQETYPIL |
|---|
| Publication date in RUNG: | 08.03.2023 |
|---|
| Views: | 2935 |
|---|
| Downloads: | 0 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
