Enhancing Solutions Of Capacity Vehicle Routing Problem Based On An Improvement Ant Colony System Algorithm

• Main Authors: Mutar, Modhi Lafta, Mohd Aboobaider, Burhanuddin, Hameed, Asaad Shakir, Yusof, Norzihani
• Format: Article
• Language: English
• Published: Institute Of Advanced Scientific Research, Inc. 2019
• Subjects: Q Science (General); QA Mathematics
• Online Access: http://eprints.utem.edu.my/id/eprint/24055/2/EnhancingSolutions%20Of%20Capacity%20Vehicle%20Routing%20Problem%20Based%20On%20An%20Improvement%20Ant%20Colony%20System%20Algorithm.pdf; http://eprints.utem.edu.my/id/eprint/24055/; https://jardcs.org/abstract.php?id=242

The Vehicle Routing Problem (VRP) is a famous routing issue and combinatorial optimization problem. It serves an important task in logistics and supply procession administration appropriate toward its wide applications in transport, product delivery, and services. VRP is one of the major important issues have no perfect solutions yet. Several authors over the last only some decades have recognized many types of research and used several algorithms with various methods to solve it. In this work the problem of the VRP work is described as follows: the vehicles which are used for transportation products toward instance place. Each vehicle begins from a major area at various times every day. The capacitated vehicle routing problem (CVRP) is described as toward service a set of delivery customers by means of well-known demands, the aim of CVRP is toward giving every vehicle with a series of delivers so with the purpose of each and every one of customers are serviced, and the cost of traveling for vehicles are decreased. The paper aims to discover an optimal route for VRP by using Improvement Ant Colony System Algorithm (IACS). Optimal routes are founded based on to decrease the distance and the time for each and every one route which directs to quickest the moving of customers to their locations, also based on developing the CVRP model for optimizing the routing issues. The IACS method has been mostly considered recently for handling several combinatorial optimization issues. In this paper, the IACS has been introduced for solving the CVRP. A wide numerical experiment has been performed on benchmark issues available in recent work. The results have been shown the IACS algorithm is better when compared to conventional metaheuristic methods for handling CVRP.