@conference { ISI:000392439200016,
title = {Generalization of capacitated p-median location problem: modeling and resolution},
booktitle = {PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL CONFERENCE ON LOGISTICS OPERATIONS MANAGEMENT (GOL{\textquoteright}16)},
year = {2016},
note = {3rd IEEE International Conference on Logistics Operations Management (GOL), Fes, MOROCCO, MAY 23-25, 2016},
publisher = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
organization = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
abstract = {The capacitated p-median location problem (CPMP) is very famous in literature and widely used within industry scope. However, in some cases, this location problem variant has poor management of capacity resources. In fact, the capacity used by facilities is fixed and not dependent on customers{\textquoteright} demands. The budget constraint Multi-Capacitated Location Problem (MCLP), considered in that paper, is a generalization of the CPMP problem, it is characterized by allowing each facility to be open with different capacities. In this paper, we will discuss the mathematical modeling of the MCLP problem, then we suggest adapted solving methods. To do this, we propose to solve the MCLP problem using Branch and Cut method. This exact solving method well-known, will serve us to test and validate our new problem formulation. Then we will build one heuristic algorithm, well adapted to our problem, it will be called GCDF (Greatest Customer Demand First). For improving solution quality, the LNS method will complete the GCDF. Computational results are presented at the end using instances that we have created under some criteria of difficulties or adapted from those of p-median problems available in literature. The GCDF{*} (GCDF improved) algorithm is fast and provides good results for most degree of difficulty instances, but it is unreliable for very specific cases. To remedy this problem, the method must start with a basic feasible solution determined by one of the reliable method such as Branch and Bound.},
isbn = {978-1-4673-8571-8},
author = {El Amrani, Mohammed and Benadada, Youssef and Gendron, Bernard},
editor = {Alaoui, AE and Benadada, Y and Boukachour, J}
}
@conference { ISI:000392439200008,
title = {Strategic planning problem represented by a three-echelon logistics network-modeling and solving},
booktitle = {PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL CONFERENCE ON LOGISTICS OPERATIONS MANAGEMENT (GOL{\textquoteright}16)},
year = {2016},
note = {3rd IEEE International Conference on Logistics Operations Management (GOL), Fes, MOROCCO, MAY 23-25, 2016},
publisher = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
organization = {Sidi Mohammed Ben Abdellah Univ Fes, Fac Sci \& Technol; Mohammed V Univ Rabat, ENSIAS Sch; Univ Havre; IEEE},
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. Our work consists, then to optimize a multi-scales and multi-periods location-distribution problem. The problem belongs to the FLNP family with a complexity of order of NP-difficult. The objective of our problem MIP is to maximize the incomes of a production company via the minimization of costs: the cost of supplying, the cost of producing and the cost of transportation. Several aspects would be treated in this subject: the horizon of planning -multi-periods and the structure of network (multi-echelons). Based on the limits of exact methods, we have proposed to resolve this problem on the basis of a heuristic method, the choice which seems to be the most adequate for our problem is LNS (Large Neighborhood Search). It is in this perspective that we have reformulated our model {[}12] in order to be represented under the form of a logistic network based on paths before the application of LNS.},
isbn = {978-1-4673-8571-8},
author = {Hamada, Yahya and Benadada, Youssef and Gendron, Bernard},
editor = {Alaoui, AE and Benadada, Y and Boukachour, J}
}