research-article

Ant Colony system approach for dynamic vehicles routing problem multi tours

Authors:

Khaoula Ouaddi,

Youssef Benadada,

Fatima Zahra MhadaAuthors Info & Claims

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

Article No.: 109, Pages 1 - 6

https://doi.org/10.1145/3090354.3090466

Published: 29 March 2017 Publication History

Abstract

In reality, many transport companies give the possibility to use an overtime to complete the service. However, this concept is less treated in the literature of the VRP in general and of the DVRP in particular. This paper presents an approach, based on the ant colony system, which treats this concept for multi-tours DVRP. A mathematical model of this variable is then proposed. Computational results are given in a version without overtime in addition to some first results of the version with overtime.

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Cited By

Wang FLiao FLi YYan XChen X(2021)An ensemble learning based multi-objective evolutionary algorithm for the dynamic vehicle routing problem with time windowsComputers & Industrial Engineering10.1016/j.cie.2021.107131154(107131)Online publication date: Apr-2021
https://doi.org/10.1016/j.cie.2021.107131

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Ant Colony system approach for dynamic vehicles routing problem multi tours

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cover image ACM Other conferences

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

March 2017

685 pages

ISBN:9781450348522

DOI:10.1145/3090354

Conference Chairs:
Mohamed Lazaar
ENSA, Tetuan, Morocco
,
Youness Tabii
ENSA, Tetuan, Morocco
,
Mohamed Chrayah
ENSA, Tetuan - Morocco
,
Mohammed Al Achhab
ENSA, Tetuan, Morocco

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Ministère de I'enseignement supérieur: Ministère de I'enseignement supérieur

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2017

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BDCA'17

BDCA'17: 2nd international Conference on Big Data, Cloud and Applications

March 29 - 30, 2017

Tetouan, Morocco

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Cited By

Wang FLiao FLi YYan XChen X(2021)An ensemble learning based multi-objective evolutionary algorithm for the dynamic vehicle routing problem with time windowsComputers & Industrial Engineering10.1016/j.cie.2021.107131154(107131)Online publication date: Apr-2021
https://doi.org/10.1016/j.cie.2021.107131

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