Title: Applying the ant colony optimisation algorithm to the capacitated multi-depot vehicle routing problem

Authors: Petr Stodola; Jan Mazal

Addresses: Department of Tactics, University of Defence, Kounicova 65, Brno, Czech Republic ' Department of Tactics, University of Defence, Kounicova 65, Brno, Czech Republic

Abstract: The multi-depot vehicle routing problem (MDVRP) is an extension of a classic vehicle routing problem (VRP). There are many heuristic and metaheuristic algorithms (e.g., tabu search, simulated annealing, genetic algorithms) as this is an NP-hard problem and, therefore, exact methods are not feasible for more complex problems. Another possibility is to adapt the ant colony optimisation (ACO) algorithm to this problem. This article presents an original solution of authors to the MDVRP problem via ACO algorithm. The first part deals with the algorithm including its principles and parameters. Then several examples and experiments are shown.

Keywords: multi-depot VRP; vehicle routing problem; MDVRP; ant colony optimisation; ACO; bio-inspired computation.

DOI: 10.1504/IJBIC.2016.078639

International Journal of Bio-Inspired Computation, 2016 Vol.8 No.4, pp.228 - 233

Received: 11 Jun 2014
Accepted: 26 Apr 2015
Published online: 30 Aug 2016 *

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