@article {Ouaddi2022205,
	title = {Heuristic based on iterative exact method for multi-tour dynamic vehicle routing problem with overtime},
	journal = {International Journal of Logistics Systems and Management},
	volume = {41},
	number = {1-2},
	year = {2022},
	note = {cited By 0},
	pages = {205-224},
	abstract = {In the last two decades, the DVRP has received a very particular interest from researchers. Because of its great utility in modern transport systems, the DVRP is now a very motivating and still attractive line of research for new studies. The complexity of this problem comes from the fact that it belongs to the VRP family in addition to the dynamism of its components. In this article, a very little studied variant of the DVRP is dealt with. This is the multi-tour DVRP with overtime (MTDVRPOT). We treat this problem from a multi-objective point of view, based on a bi-objective mathematical modelling. The first objective is to minimise the total travelled distance, while the second objective is to minimise to maximal performed overtime. A heuristic based on the iterative exact method was proposed to solve this problem. Its principle is to divide the working day into time periods and resolve iteratively the mathematical models. Each mathematical model corresponds to one subproblem of one time period. Copyright {\textcopyright} 2022 Inderscience Enterprises Ltd.},
	doi = {10.1504/IJLSM.2022.120999},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125744703\&doi=10.1504\%2fIJLSM.2022.120999\&partnerID=40\&md5=57f923c1d5d485989c02ebc34053a4c1},
	author = {Ouaddi, K. and Benadada, Y. and Mhada, F.-Z.}
}
@conference {Ouaddi2020,
	title = {A comparative study of three methods for solving the Mutli-Trip Dynamic Vehicle Routing Problem with Overtime (MTDVRPOT)},
	booktitle = {Proceedings - 2020 5th International Conference on Logistics Operations Management, GOL 2020},
	year = {2020},
	note = {cited By 0},
	abstract = {In recent years, the dynamic vehicle routing problem (DVRP) and its variants have been increasingly studied and several resolution approaches have been proposed. The objective of this study is to compare the results of three different approaches designed for the multi-trip dynamic vehicle routing problem with overtime (MTDVRPOT). The first approach is based on an exact method, the second is a hybrid ant colony system, while the third is a memetic algorithm. The tests are performed on small instances, and the results show the efficiency of the memetic algorithm. {\textcopyright} 2020 IEEE.},
	keywords = {Ant colony optimization, Comparative studies, Dynamic vehicle routing problems, Exact methods, Hybrid ant colony systems, Memetic algorithms, Multi trips, Vehicle routing, Vehicles},
	doi = {10.1109/GOL49479.2020.9314727},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100211299\&doi=10.1109\%2fGOL49479.2020.9314727\&partnerID=40\&md5=b18f63526f7e1ac4b3feb37e42ce0faa},
	author = {Ouaddi, K. and Mhada, F.-Z. and Benadada, Y.}
}
@article {Ouaddi2020643,
	title = {Memetic algorithm for multi-tours dynamic vehicle routing problem with overtime (Mdvrpot)},
	journal = {International Journal of Industrial Engineering Computations},
	volume = {11},
	number = {4},
	year = {2020},
	note = {cited By 8},
	pages = {643-662},
	abstract = {After three decades of its introduction, the dynamic vehicle routing problem (DVRP) remains a fertile field for new studies. The technological evolution, which continues to progress day by day, has allowed better communication between different actors of this model and a more encouraging execution time. This encouraged researchers to investigate new variants of the DVRP and use more complicated algorithms for the resolution. Among these variants is the multi-tour DVRP (MTDVRP) with overtime (MTDVRPOT), which is the subject of this article. This paper proposes an approach with a memetic algorithm (MA). The results obtained in this study are better than those of the ant colony system (ACS) applied to the same problem and published in an earlier paper. {\textcopyright} 2020 by the authors; licensee Growing Science, Canada.},
	doi = {10.5267/j.ijiec.2020.4.001},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090725004\&doi=10.5267\%2fj.ijiec.2020.4.001\&partnerID=40\&md5=d438b38f932a7acfddc0489585ccfa79},
	author = {Ouaddi, K. and Mhada, F.-Z. and Benadada, Y.}
}
@article {Ouaddi2018306,
	title = {Ant colony system for dynamic vehicle routing problem with overtime},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {9},
	number = {6},
	year = {2018},
	pages = {306-315},
	doi = {10.14569/IJACSA.2018.090644},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049537762\&doi=10.14569\%2fIJACSA.2018.090644\&partnerID=40\&md5=05f62f74b7943a59ae4ebc2b7d73e82e},
	author = {Ouaddi, K. and Benadada, Y. and Mhada, F.-Z.}
}
@conference {Ouaddi2017,
	title = {Ant colony system approach for dynamic vehicles routing problem multi tours},
	booktitle = {ACM International Conference Proceeding Series},
	volume = {Part F129474},
	year = {2017},
	note = {cited By 0},
	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. {\textcopyright} 2017 Association for Computing Machinery.},
	doi = {10.1145/3090354.3090466},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028464197\&doi=10.1145\%2f3090354.3090466\&partnerID=40\&md5=8544fa68e8eb6ee3c79230c16618f329},
	author = {Ouaddi, K. and Benadada, Y. and Mhada, F.Z.}
}
@conference {Ouaddi2016,
	title = {Multi period dynamic vehicles routing problem: Literature review, modelization and resolution},
	booktitle = {Proceedings of the 3rd IEEE International Conference on Logistics Operations Management, GOL 2016},
	year = {2016},
	note = {cited By 0},
	abstract = {Being member of the VRP family, the Dynamic VRP (DVRP) has been a topic of interest in the realm of research, especially in the last decade. The steps of resolution were based on various approaches, ranging from the exact meta-heuristic to customized methods. This paper presents a literature review of the DVRP by classifying relevant studies according to the adopted approach of resolution. The dynamic extension of a version already present in the literature of the turned VRP multi classical is described then. A mathematical modeling is proposed for this extension. For the resolution of our problem, we adopted an approach based on the system of the colony of ants. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/GOL.2016.7731706},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85001930738\&doi=10.1109\%2fGOL.2016.7731706\&partnerID=40\&md5=a7ddfd023d856f524eb379bb4ae1805a},
	author = {Ouaddi, K. and Benadada, Y. and Mhada, F.-Z.}
}
