ACO and CP Working Together to Build a Flexible Tool for the VRP

Negar ZakeriNejad, Daniel Riera, Daniel Guimarans


In this paper a flexible hybrid methodology, combining Ant Colony Optimisation (ACO) and Constraint Programming (CP), is presented for solving Vehicle Routing Problems (VRP). The stress of this methodology is on the word ‘flexible’: It gives reasonably good results to changing problems without high solution redesign efforts. Thus a different problem with a new set of constraints and objectives requires no changes to the search algorithm. The search part (driven by ACO) and the model of the problem (included in the CP part) are separated to take advantage of their best attributes. This separation makes the application of the framework to different problems much simpler. To assess the feasibility of our approach, we have used it to solve different instances of the VRP family. These instances are built by combining different sets of constraints. The results obtained are promising but show that the methodology needs deeper communication between ACO and CP to improve its performance.


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Paper Citation

in Harvard Style

ZakeriNejad N., Riera D. and Guimarans D. (2016). ACO and CP Working Together to Build a Flexible Tool for the VRP . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 122-129. DOI: 10.5220/0005668101220129

in Bibtex Style

author={Negar ZakeriNejad and Daniel Riera and Daniel Guimarans},
title={ACO and CP Working Together to Build a Flexible Tool for the VRP},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - ACO and CP Working Together to Build a Flexible Tool for the VRP
SN - 978-989-758-171-7
AU - ZakeriNejad N.
AU - Riera D.
AU - Guimarans D.
PY - 2016
SP - 122
EP - 129
DO - 10.5220/0005668101220129