@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:000392439200048, 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{\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 = {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.}, isbn = {978-1-4673-8571-8}, author = {Ouaddi, Khaoula and Benadada, Youssef and Mhada, Fatima-Zahra}, editor = {Alaoui, AE and Benadada, Y and Boukachour, J} } @conference { ISI:000392439200021, title = {New approaches for solving the container stacking problem}, 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 = {Containers shipment has grown very fast during the last ten years, in Tanger Med port for example, 3Millions containers (80\% in transshipment) TEUs (Twenty feet equivalent unit) has been changed during 2015 (Tanger Med Port authority {\textquoteleft}{\textquoteleft}TMPA{{\textquoteright}{\textquoteright}} study March{\textquoteright} 2016 {[} 1]), which correspond to an increase of 40\% comparing with the last study made in 2012. Thus, our study will deal with the port management and the improvement of the operations processes. The aim of this paper is to define a new strategies to solve the container stacking problem (CSP) using an approach of optimization. Thus we define a new MIP (Mathematical Integer Program) to deal with the operational tasks in a containers terminal. In which we optimize the number of the stacks used to store a given number of inbound containers and also we minimize the related cost of the traveling distance for inbound containers between the sea side and the yard side. This paper is organized as follow: we introduce and locate first our problem, then we present the literature review of the CSP. The problem definition and the MIP introduction will be the subject of the next section, and we finish by presenting the findings and the future perspectives. As a proposed resolution approach for our MIP, we propose a developed genetic algorithm strategy (DGAS) as a metaheuristic and the Branch \& Cut (B\&C) as an exact method. Our main objective is to avoid reshuffles and to find out the best yard configuration to store inbound containers. The DGAS will be applied to an existing instances in the literature, and the obtained numerical results is compared with the Cplex results (B\&C). The main inputs for our proposed framework are the height, weight, destination, type containers \& yard bays, and the expected departure time (EDT). Our objective at the end is to have an optimized guide to the planners to easily define the unloading plan and the storage position for each container, giving an initial stacking state and a container demand.}, isbn = {978-1-4673-8571-8}, author = {Razouk, Chafik and Benadada, Youssef and Boukachour, Jaouad}, editor = {Alaoui, AE and Benadada, Y and Boukachour, J} } @conference { ISI:000392439200025, title = {Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem}, 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 = {Aircraft Maintenance Routing (AMR) is one of the major optimization problems in the airline industry. In this study, we present a mathematical formulation for the daily AMR problem which aims to minimize the risk of both scheduled and non-scheduled maintenance costs. Exact methods may fail to deal with such problems. Our contribution is then to examine the use of an improved particle swarm optimization (PSO) algorithm by a uniform mutation operator for solving this probabilistic problem. Computational results show that our hybrid approach gives competitive results comparing to the native binary PSO.}, isbn = {978-1-4673-8571-8}, author = {Sarhani, Malek and Ezzinbi, Omar and El Afia, Abdellatif and Benadada, Youssef}, 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} } @conference { ISI:000346582400023, title = {Evolutionary algorithm for a Green vehicle routing problem with multiple trips}, booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)}, year = {2014}, note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014}, pages = {148+}, publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, abstract = {This paper deals with a variant of vehicle routing problem where vehicles are allowed to take more than one route during the working day. The depreciation of the vehicle may be a bad investment for green transportation because it could generate more emissions. Hence, it is necessary to satisfy green transportation requirements by reducing the CO2 emissions from road transportation. The objective is to optimize the amount of greenhouse gas emissions. A restricted fleet size is used to serve demands, so the vehicles could exceed the time horizon. It is subject also to minimize the maximum overtime to find feasible solutions. A mathematical model has been proposed for the Green Vehicle Routing Problem with multiple trips (GVRPM). An evolutionary algorithm has been developed to solve it by combining a genetic algorithm with a local search procedure. The effectiveness of our approach is tested on a set of benchmarks. Comparing with existing algorithm, our approach shows competitive performance and contributes many new best solutions.}, isbn = {978-1-4799-4650-1}, author = {Ayadi, Rajaa and ElIdrissi, Adiba ElBouzekri and Benadada, Youssef and Alaoui, Ahmed El Hilali}, editor = {Benadada, Y} } @conference { ISI:000346582400012, title = {Exact method for the multi-region vehicle routing problem in large quantities by a heterogeneous fleet of vehicles}, booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)}, year = {2014}, note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014}, pages = {70-78}, publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, abstract = {This article describes an exact method based on a Branch \& Cut algorithm for the multi-region vehicle routing problem in large quantities by a heterogeneous fleet of vehicles. Test results on different problem instances are presented after have been solved by CPLEX.}, isbn = {978-1-4799-4650-1}, author = {Benslimane, Mohammed Taha and Benadada, Youssef}, editor = {Benadada, Y} } @conference { ISI:000346582400008, title = {A metaheuristic approach for solving the airline maintenance routing with aircraft on ground problem}, booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)}, year = {2014}, note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014}, pages = {48+}, publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, abstract = {In the airline industry, the Aircraft Maintenance Routing (AMR) problem has been one of the great successes of operations research. The AMR problem is to determine a particular route for each aircraft to undergo different levels of maintenance checks. The objective is to minimize the total maintenance costs. In this study, our aim is to present a mathematical formulation for the AMR problem which takes into account the case of Aircraft On Ground (AOG). We develop solution approaches based on Particle Swarm Optimization algorithm and Genetic algorithm for solving the problem. The results show the effectiveness of this solution in reducing computational time.}, isbn = {978-1-4799-4650-1}, author = {Ezzinbi, Omar and Sarhani, Malek and El Afia, Abdellatif and Benadada, Youssef}, editor = {Benadada, Y} } @conference { ISI:000346582400009, title = {Particle swarm optimization algorithm for solving airline crew scheduling problem}, booktitle = {PROCEEDINGS OF 2014 2ND IEEE INTERNATIONAL CONFERENCE ON LOGISTICS AND OPERATIONS MANAGEMENT (GOL 2014)}, year = {2014}, note = {2nd IEEE International Conference on Logistics Operations Management (GOL), Rabat, MOROCCO, JUN 05-07, 2014}, pages = {52-56}, publisher = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, organization = {IEEE; Mohammed VI Souissi Univ, ENSIAS Sch; Univ Le Havre; Sidi Mohamed Ben Abdellah Univ, FST}, abstract = {In air transport, the cost related to crew members presents one of the most important cost supported by airline companies. The objective of the crew scheduling problem is to determine a minimum-cost set of pairings so that every flight leg is assigned a qualified crew and every pairing satisfies the set of applicable work rules. In this paper, we propose a solution for the crew scheduling problem with Particle Swarm Optimization (PSO) algorithm, this solution approach is compared with the Genetic Algorithm (GA) for both crew pairing and crew assignment problems which are the two part of crew scheduling problem.}, isbn = {978-1-4799-4650-1}, author = {Ezzinbi, Omar and Sarhani, Malek and El Afia, Abdellatif and Benadada, Youssef}, editor = {Benadada, Y} } @article { ISI:000337796300005, title = {Ant Colony Algorithm for the Multi-Depot Vehicle Routing Problem in Large Quantities by a Heterogeneous Fleet of Vehicles}, journal = {INFOR}, volume = {51}, number = {1, SI}, year = {2013}, month = {FEB}, pages = {31-40}, abstract = {This article describes a heuristic method based on an ant colony algorithm for the multi-depot vehicle routing problem in large quantities by a heterogeneous fleet of vehicles. Test results on different problem instances are presented and compared with those obtained by CPLEX and by a previous constructive heuristic.}, issn = {0315-5986}, doi = {10.3138/infor.51.1.31}, author = {Benslimane, Mohammed Taha and Benadada, Youssef} } @article {9434372520130201, title = {Ant colony algorithm for the multi-depot vehicle routing problem in large quantities by a heterogeneous fleet of vehicles.}, journal = {INFOR}, volume = {51}, number = {1}, year = {2013}, pages = {31 - 40}, abstract = {This article describes a heuristic method based on an ant colony algorithm for the multi-depot vehicle routing problem in large quantities by a heterogeneous fleet of vehicles. Test results on different problem instances are presented and compared with those obtained by CPLEX and by a previous constructive heuristic. [ABSTRACT FROM AUTHOR]}, keywords = {Ant algorithms, ant colony algorithm, Comparative studies, Computer networks, Heuristic algorithms, Information technology, Keywords Distribution, products in large quantities, Vehicle routing problem}, issn = {03155986}, url = {http://search.ebscohost.com/login.aspx?direct=true\&db=bth\&AN=94343725\&site=ehost-live}, author = {Benslimane, Mohammed Taha and Benadada, Youssef} } @conference { ISI:000326538300126, title = {Combined optimization of shipping and storage costs in a multi-product and multi-level supply chain, under a stochastic demand}, booktitle = {2013 5TH INTERNATIONAL CONFERENCE ON MODELING, SIMULATION AND APPLIED OPTIMIZATION (ICMSAO)}, year = {2013}, note = {5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), Hammamet, TUNISIA, APR 28-30, 2013}, abstract = {The increasing need for optimality in the presence of uncertainty motivates the development and application of Model Predictive Control. In this paper we apply the Stochastic Model Predictive Control to optimize the cost of storage and transport for a multi-product and a multi-level supply chain under a stochastic demand. We use the dynamic programming to find the control policies resolving the problem.}, isbn = {978-1-4673-5814-9; 978-1-4673-5812-5}, author = {Tikito, Kawtar and Achchab, Said and Benadada, Youssef} }