@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 {Hamada20172084,
	title = {A hybrid approach for a strategic planning problem represented by a three-echelon logistics network},
	booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management},
	year = {2017},
	note = {cited By 0},
	pages = {2084-2085},
	abstract = {This article aims to elaborate a strategic plan allowing to decision makers to take right decisions (Selecting suppliers, Selecting plants that can produce a specific product,..) in the right moment in order to minimize the generated costs It is in this context that our work is being taken. The objective is to model and solve a strategic planning problem at three levels which are: supplier-plant, plant-plant and plant-customer. The costs taken into effect in this model are: the supply costs, production costs and transport costs. The problem belongs to the CFLP Family (Capacitated Facility Location Problem) with a NPhard complexity. The objective of our MIP problem is to maximize a production company benefits through minimizing costs mentioned above. Given the limitations of exact methods and the optimum local problem when we used a heuristic method like a LNS (Large Neighborhood Search), we proposed to solve this problem using hybridization between two heuristics: LNS \& Genetic Algorithm This hybridization will give us more opportunities to find better solution when a local optimum is reached. {\textcopyright} IEOM Society International.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018996488\&partnerID=40\&md5=986399337bcb183f863d9133bfa92170},
	author = {Hamada, Y. and Benadada, Y. and Gendron, B.}
}
@conference {Chafik20171983,
	title = {A hybrid bin-packing algorithm for solving the yard optimization problem},
	booktitle = {Proceedings of the International Conference on Industrial Engineering and Operations Management},
	year = {2017},
	note = {cited By 0},
	pages = {1983-1991},
	abstract = {Maritime container terminals are facilities where cargo containers are transshipped between ships or between ships and land vehicles (tucks or trains). They can be automated; semi-automated or static ones depend on the type of the equipments that they contain. There are crucial resources at container terminals; the yard, cranes and the vehicles. The yard refers to the temporary storage area where inbound, outbound containers can be stored. While we have two kinds of cranes depending on the type of the yard we are working on: yard crane and quay crane. Vehicles are used to transfer the container between the seaside and yard side (the external trucks XTs are not considerable in our study). The decision of the container stacking position is the most important operational task for the incoming containers which affects not only the productivity of the stacking but also for the later retrieval and also to avoid the unproductive moves to access to the requested containers stored in the stack. Our aim is to define a new approach to design the container stacking problem using an approach of optimization and simulation. Thus in this paper we will define a new MIP which has as objective the minimization of the number of the stacks used to store a given number of inbound containers, and to define afterwards a simulation model using a simulation software (Arena) which has as input the result of the optimization model. So we will try first to define a relocation model using the standard (FCFS) then the Best fit decrease (BFD) from the bin packing algorithm to store and maintain the storage area and to avoid unproductive moves and reshuffles to find out the requested container sequence. The main inputs are high, weight, destination and the delivery time of each container. Our objective is to have, based on heuristics, a guide to the planner to obtain an optimized stacking / reshuffling plan, given a stacking state and a container demand. We will try to minimize the number of reshuffles as well as the number of stacks used and obtaining a conclusion about possible yard configurations. {\textcopyright} IEOM Society International.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019000218\&partnerID=40\&md5=9aebf3bb53d265a1dd55c143dac817a3},
	author = {Chafik, R. and Benadada, Y. and Boukachour, J.}
}
