Title :
An Ant Colony Algorithm with Stochastic Local Search for the VRP
Author_Institution :
Coll. of Autom., Beijing Union Univ., Beijing
Abstract :
In recent years there has been growing interest in algorithms inspired by the observation of natural phenomena to define computational procedures which can solve complex problems. In this paper, through an analysis of the constructive procedure of the solution in the ant colony system (ACS), a vehicle routing problem (VRP) is examined and a hybrid ant colony system coupled with a stochastic local search algorithm(SLSACS), is proposed. In SLSACS, only partial customers are randomly chosen to compute the transition probability. Experiments on various aspects of the algorithm and computational results for fourteen benchmark problems are reported. We compare our approach with ACS, some other classic, powerful meta-heuristics and show that our results are competitive.
Keywords :
optimisation; probability; search problems; stochastic processes; transportation; ant colony algorithm; ant colony system; stochastic local search algorithm; transition probability; vehicle routing problem; Algorithm design and analysis; Ant colony optimization; Automation; Cities and towns; Educational institutions; Routing; Stochastic processes; Stochastic systems; Traveling salesman problems; Vehicles;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.130