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2013 (Vol. 6, Issue: 05)
Article Information:

Adaptive Ant Colony Algorithm for the VRP Solution of Logistics Distribution

Yu-Ping Wang
Corresponding Author:  Yu-Ping Wang 

Key words:  Ant colony algorithm, information entropy, pare to local search, vehicle routing problem, , ,
Vol. 6 , (05): 807-811
Submitted Accepted Published
September 13, 2012 October 24, 2012 June 25, 2013

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.
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  Cite this Reference:
Yu-Ping Wang, 2013. Adaptive Ant Colony Algorithm for the VRP Solution of Logistics Distribution.  Research Journal of Applied Sciences, Engineering and Technology, 6(05): 807-811.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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