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Authors: S. Ben Hamida 1 ; R. Gorsane 2 and K. Gorsan Mestiri 2

Affiliations: 1 LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, France ; 2 InstaDeep, Tunisia

Keyword(s): Genetic Algorithms, Ordering Optimization, CVRP, Hybridization, Exploitation/Exploration.

Abstract: Genetic Algorithms (GA) have long been used for ordering optimization problems with some considerable efforts to improve their exploration and exploitation abilities. A great number of GA implementations have been proposed varying from GAs applying simple or advanced variation operators to hybrid GAs combined with different heuristics. In this work, we propose a short review of genetic operators for ordering optimization with a classification according to the information used in the reproduction step. Crossover operators could be position (”blind”) operators or heuristic operators. Mutation operators could be applied randomly or using local optimization. After studying the contribution of each class on solving two benchmark instances of the Capacitated Vehicle Routing Problem (CVRP), we explain how to combine the variation operators to allow simultaneously a better exploration of the search space with higher exploitation. We then propose the random and the balanced hybridization of t he operators’ classes. The hybridization strategies are applied to solve 24 CVRP benchmark instances. Results are analyzed and compared to demonstrate the role of each class of operators in the evolution process. (More)

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Paper citation in several formats:
Ben Hamida, S. ; Gorsane, R. and Mestiri, K. (2020). Towards a Better Understanding of Genetic Operators for Ordering Optimization: Application to the Capacitated Vehicle Routing Problem. In Proceedings of the 15th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-443-5; ISSN 2184-2833, SciTePress, pages 461-469. DOI: 10.5220/0009832704610469

@conference{icsoft20,
author={S. {Ben Hamida} and R. Gorsane and K. Gorsan Mestiri},
title={Towards a Better Understanding of Genetic Operators for Ordering Optimization: Application to the Capacitated Vehicle Routing Problem},
booktitle={Proceedings of the 15th International Conference on Software Technologies - ICSOFT},
year={2020},
pages={461-469},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009832704610469},
isbn={978-989-758-443-5},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Software Technologies - ICSOFT
TI - Towards a Better Understanding of Genetic Operators for Ordering Optimization: Application to the Capacitated Vehicle Routing Problem
SN - 978-989-758-443-5
IS - 2184-2833
AU - Ben Hamida, S.
AU - Gorsane, R.
AU - Mestiri, K.
PY - 2020
SP - 461
EP - 469
DO - 10.5220/0009832704610469
PB - SciTePress

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