Ant colony optimization (ACO) meta-heuristic solving the vehicle scheduling problem (VSP)

Authors:
Aristidis Vlachos;Aspasia Moue
Affiliations:
Merchant Marine Academy of Aspropyrgos, Engineering Department, Aspropyrgos, Greece;Merchant Marine Academy of Aspropyrgos, Engineering Department, Aspropyrgos, Greece
Venue:
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Year:
2006

Citing 5
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Ant Colony Optimization

Ant Colony Optimization

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Abstract

Ant Colony Optimization (ACO) is a branch of a newly developed form of artificial intelligence called swarm intelligence. Swarm intelligence is a technique that studies the collective behavior of a decentralized system made up by a population of simple agents interacting locally with each other and with their environment. Ant Colony algorithms have been applied successfully to Combinatorial Optimization Problems. In this paper we focus on the definition and minimization of the objective function of the VSP using the Diversified Form of the Ant Colony System algorithm (DFACS). The algorithm DFACS was implemented for an eight node-city graph with respective demands.