Research Article | OPEN ACCESS
Adaptive Ant Colony Algorithm for the VRP Solution of Logistics Distribution
Yu-Ping Wang
College of Automation, Beijing Union University, China
Research Journal of Applied Sciences, Engineering and Technology 2013 5:807-811
Received: September 13, 2012 | Accepted: October 24, 2012 | Published: June 25, 2013
Abstract
In order to conquer the premature convergence problem and lower the cost of computing of the basic Ant Colony Algorithm (ACA), we present an adaptive ant colony algorithm, named AACA, coupled with a Pareto Local Search (PLS) algorithm and apply to the Vehicle Routing Problem (VRP) and Capacitated VRP (CVRP). By using the information entropy, the algorithm adjusts the pheromone updating strategy adaptively. Experiments on various aspects of the algorithm and computational results for some benchmark problems are reported. We compare our approach with some classic, powerful meta-heuristics and show that the proposed approach can obtain the better quality of the solutions.
Keywords:
Ant colony algorithm, information entropy, pare to local search, vehicle routing problem,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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