Multi-Objectives Ant Colony System For Solving Multi-Objectives Capacitated Vehicle Routing Problem

Mutar, Modhi Lafta and Mohd Aboobaider, Burhanuddin and Hameed, Asaad Shakir and Yusof, Norzihani and Jabbar Mohammed, Ali Abdul and Alrifaie, Mohammed F. (2020) Multi-Objectives Ant Colony System For Solving Multi-Objectives Capacitated Vehicle Routing Problem. Journal of Theoretical and Applied Information Technology, 98 (24). pp. 4014-4027. ISSN 1992-8645

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Abstract

As a combinatorial optimization problem, the capacitated vehicle routing problem (CVRP) is a vital one in the domains of distribution, transportation and logistics. Despite the fact that many researchers have solved the problem using a single objective, only little attention has been given to multi-objective optimization. As compared to multi-objectives, the comparison of solutions is easier with single-objective optimization fitness function. In this paper, the following objectives were achieved: (i) in view of the domain of the multiobjective CVRP, the total distance traveled by the vehicles and the total number of vehicles used are reduced, and (ii) in the view of the technique, a multi-objective Ant Colony System is proposed to solve the multiobjective of CVRP based on the experience of sub-paths. The proposed algorithm was evaluated using some standard benchmark problems of CVRP. The results show that the algorithm which has been proposed in this study is highly competitive and quite effective for multi-objective optimization of CVRP

Item Type:	Article
Uncontrolled Keywords:	Combinatorial Optimization Problem, Ant Colony System Algorithm, Capacitated Vehicle Routing Problem, Multi-Objectives Capacitated Vehicle Routing Problem)
Divisions:	Faculty of Information and Communication Technology
Depositing User:	F Haslinda Harun
Date Deposited:	26 Aug 2021 15:44
Last Modified:	26 Aug 2021 15:44
URI:	http://eprints.utem.edu.my/id/eprint/25274
Statistic Details:	View Download Statistic

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