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Constraint Programming Based Algorithm for Solving Large-Scale Vehicle Routing Problems

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Hybrid Artificial Intelligent Systems (HAIS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11734))

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Abstract

Smart cities management has become currently an interesting topic where recent decision aid making algorithms are essential to solve and optimize their related problems. A popular transportation optimization problem is the Vehicle Routing Problem (VRP) which is high complicated in such a way that it is categorized as a NP-hard problem. VRPs are famous and appear as influential problems that are widely present in many real-world industrial applications. They have become an elemental part of economy, the enhancement of which arises in a significant reduction in costs.

The basic version of VRPs, the Capacitated VRP (CVRP) occupies a central position for historical and practical considerations since there are important real-world systems can be satisfactorily modeled as a CVRP. A Constraint Programming (CP) paradigm is used to model and solve the CVRP by applying interval and sequence variables in addition to the use of a transition distance matrix to attain the objective. An empirical study over 52 CVRP classical instances, with a number of nodes that varies from 16 to 200, and 20 CVRP large-scale instances, with a number of nodes that varies from 106 to 459, shows the relative merits of our proposed approach. It shows also that the CP paradigm tackles successfully large-scale problems with a percentage deviation varying from 2% to 10% where several exact and heuristic algorithms fail to tackle them and only a few meta-heuristics can probably solve instances with a such big number of customers.

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Notes

  1. 1.

    http://neo.lcc.uma.es/radi-aeb/WebVRP/Problem_Instances/CVRPInstances.html.

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Author information

Authors and Affiliations

  1. Institut Supérieur de Gestion de Tunis, Université de Tunis, Cité Bouchoucha, 2000, Tunis, Tunisia

    Bochra Rabbouch

  2. Laboratoire d’Algèbre, Théorie de Nombres et Analyse Non-linéaire, Faculté des Sciences, University of Monastir, 5019, Monastir, Tunisia

    Bochra Rabbouch & Foued Saâdaoui

  3. Department of Statistics, Faculty of Sciences, King Abdulaziz University, P.O. BOX 80203, Jeddah, 21589, Saudi Arabia

    Foued Saâdaoui

  4. Ecole Supérieure de Commerce de Tunis, Université de Manouba, Campus Universitaire de La Manouba, 2010, Tunis, Tunisia

    Rafaa Mraihi

Authors
  1. Bochra Rabbouch
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  2. Foued Saâdaoui
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  3. Rafaa Mraihi
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Corresponding author

Correspondence to Bochra Rabbouch .

Editor information

Editors and Affiliations

  1. University of León, León, Spain

    Hilde Pérez García

  2. University of León, León, Spain

    Lidia Sánchez González

  3. University of León, León, Spain

    Manuel Castejón Limas

  4. University of A Coruña, Ferrol, Spain

    Héctor Quintián Pardo

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado Rodríguez

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Rabbouch, B., Saâdaoui, F., Mraihi, R. (2019). Constraint Programming Based Algorithm for Solving Large-Scale Vehicle Routing Problems. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science(), vol 11734. Springer, Cham. https://doi.org/10.1007/978-3-030-29859-3_45

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  • DOI: https://doi.org/10.1007/978-3-030-29859-3_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29858-6

  • Online ISBN: 978-3-030-29859-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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