An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem

Modhi Lafta Mutar and Mohd Aboobaider, Burhanuddin and Asaad Shakir Hameed and Yusof, Norzihani and Hussein Jameel Mutashar (2020) An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem. International Journal of Industrial Engineering Computations, 11. pp. 549-564. ISSN 1923-2934

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Abstract

Capacitated Vehicle Routing Problem (CVRP) is considered as one of the most famous specialized forms of VRP that has attracted considerable attention from researchers. This problem belongs to complex combinatorial optimization problems included in the NP-Hard Problem category, which is a problem that needs difficult computation. This paper presents an improvement of Ant Colony System (ACS) to solve this problem. In this study, the problem deals with a few vehicles which are used for transporting products to specific places. Each vehicle starts from a main location at different times every day. The capacitated vehicle routing problem (CVRP) is defined to serve a group of delivery customers with known demands. The proposed study seeks to find the best solution of CVRP by using improvement ACS with the accompanying targets: (1) To decrease the distance as long distances negatively affect the course of the process since it consumes a great time to visit all customers. (2) To implement the improvement of ACS algorithm on new data from the database of CVRP. Through the implementation of the proposed algorithm better results were obtained from the results of other methods and the results were compared.

Item Type:	Article
Uncontrolled Keywords:	Vehicle routing problem, Capacitated vehicle routing, Problem ant colony system algorithm, Combinatorial optimization, Problems
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Sabariah Ismail
Date Deposited:	08 Jul 2021 13:27
Last Modified:	08 Jul 2021 13:27
URI:	http://eprints.utem.edu.my/id/eprint/25146
Statistic Details:	View Download Statistic

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