Mustapha Ratli - Academia.edu (original) (raw)
Papers by Mustapha Ratli
Computers & Operations Research
International Transactions in Operational Research, 2016
The multivehicle covering tour problem (m-CTP) is a transportation problem with different kinds o... more The multivehicle covering tour problem (m-CTP) is a transportation problem with different kinds of locations, where a set of locations must be visited while another set must be close enough to planned routes. Given two sets of vertices V and W, where V represents the set of vertices that may be visited and W is a set of vertices that must be covered by up to m vehicles, the m-CTP problem is to minimize vehicle routes on a subset of V including T, which represents the subset of vertices that must be visited through the use of potential locations in V. The variant of m-CTP without a route-length constraint is treated in this paper. To tackle this problem, we propose a variable neighborhood search heuristic based on variable neighborhood descent method. Experiments were conducted using the datasets based on traveling salesman problem library instances.
Le Centre pour la Communication Scientifique Directe - HAL - Diderot, 2013
Le Centre pour la Communication Scientifique Directe - HAL - Inria, Jul 1, 2013
Le Centre pour la Communication Scientifique Directe - HAL - Université Paris Descartes, Oct 1, 2019
Le Centre pour la Communication Scientifique Directe - HAL - Université Paris Descartes, Apr 1, 2016
Le Centre pour la Communication Scientifique Directe - HAL - Inria, Sep 6, 2017
Optimization Letters, Mar 3, 2022
In this article the affiliation details for the below authors were published incorrectly.
Optimization Letters, 2022
Electronic Notes in Discrete Mathematics, 2015
The vehicle routing problem with multiple trips (V RP MT) is a variants of the standard (V RP), w... more The vehicle routing problem with multiple trips (V RP MT) is a variants of the standard (V RP), where each vehicle can be used more than once during the working period. For this NP-Hard problem, we propose a variable neighborhood search Algorithm in which four neighborhood structure are designed to find the planning of trips. The algorithm was tested over a set of benchmark problems and the obtained solutions were compared with five previously proposed algorithms. Encouraging results are obtained.
Electronic Notes in Discrete Mathematics, 2015
In this article, we consider a transportation problem with different kinds of locations: V , T , ... more In this article, we consider a transportation problem with different kinds of locations: V , T , and W. The set T ⊂ V consists of vertices that must be visited through the use of potential locations in V and W consists of locations that must be covered. The problem consists in minimizing vehicle routes on a subset of V including T. We develop a variable neighborhood search heuristic based on a variable neighborhood descent in which a set of locations must be visited, whereas another subset must be close enough to the planned routes. We tested and compared our algorithm on datasets based on TSP Library instances.
Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM), 2013
We propose a hybrid approach for multi-objective assignment problem which combines genetic algori... more We propose a hybrid approach for multi-objective assignment problem which combines genetic algorithm and mathematical programming techniques. This method is based on the dominance cost variant of the multi-objective genetic algorithm hybridized with exact method. The initial population is generated by solving a series of mono-objective assignment problems obtained by a suitable choice of a set of weights. The crossover operator solves a reduced mono-objective problem where the weights are chosen to identify an unexplored region. Numerical experiments show the efficiency of our approach.
Computers & Operations Research
The parking problem has become one of the major issues in urban transportation planning and traff... more The parking problem has become one of the major issues in urban transportation planning and traffic management research. The present paper deals with the dynamic assignment problem of the parking slots (places). The objectives are to provide a global satisfaction of all customers and maximize parking occupancy. A dynamic assignment problem consists in solving a sequence of assignment problems over time. To cope with all these aspects, we offer in this paper, a new approach based on a learning strategy: an Estimation of Distribution Algorithm (EDA) where a reinforcement learning method is used to support the assignment algorithm. We tested our approach with simulations for over 120 days, using a set of up to 10 parking lots (i.e. with up to 7,000 parking slots) and 13,000 requests distributed with different patterns over a day. The comparative study between an assignment algorithm with and without reinforcement learning algorithm has proven the relevance of our approach: the saving i...
Optimization Letters, Sep 27, 2014
In this paper we consider scheduling tasks on a multiprocessor system, taking into account commun... more In this paper we consider scheduling tasks on a multiprocessor system, taking into account communication delays. We propose a new Mixed Integer Program (MIP) formulation that drastically reduces both the number of variables and the number of constraints, when compared to the best mathematical programming formulations from the literature. In addition, we propose pre-processing procedures that generates cuts and bounds on all variables, reducing the solution space of the problem as well. Cuts are obtained by using forward and backward critical path method from project management field, while the upper bound is derived from the new greedy heuristic. Computational experience shows advantages of our approach.
The parking problem is nowadays one of the major issues in urban transportation planning and traf... more The parking problem is nowadays one of the major issues in urban transportation planning and traffic management research. In fact, the consequences of the lack of parking slots along with the inadequate management of these facilities are tremendous. The aim of this thesis is to provide efficient and robust algorithms in order to save time and money for drivers and to increase the income of parking managers. The problem is formulated as a multi-objective assignment problem in static and dynamic environments. First, for the static environment, we propose new two-phase heuristics to calculate an approximation of the set of efficient solutions for a bi-objective problem. In the first phase, we generate the supported efficient set with a standard dichotomic algorithm. In the second phase we use four metaheuristics to generate an approximation of the non-supported efficient solutions. The proposed approaches are tested on the bi-objective shortest path problem and the biobjective assignme...
Journal of Global Optimization
Computers & Operations Research
International Transactions in Operational Research, 2016
The multivehicle covering tour problem (m-CTP) is a transportation problem with different kinds o... more The multivehicle covering tour problem (m-CTP) is a transportation problem with different kinds of locations, where a set of locations must be visited while another set must be close enough to planned routes. Given two sets of vertices V and W, where V represents the set of vertices that may be visited and W is a set of vertices that must be covered by up to m vehicles, the m-CTP problem is to minimize vehicle routes on a subset of V including T, which represents the subset of vertices that must be visited through the use of potential locations in V. The variant of m-CTP without a route-length constraint is treated in this paper. To tackle this problem, we propose a variable neighborhood search heuristic based on variable neighborhood descent method. Experiments were conducted using the datasets based on traveling salesman problem library instances.
Le Centre pour la Communication Scientifique Directe - HAL - Diderot, 2013
Le Centre pour la Communication Scientifique Directe - HAL - Inria, Jul 1, 2013
Le Centre pour la Communication Scientifique Directe - HAL - Université Paris Descartes, Oct 1, 2019
Le Centre pour la Communication Scientifique Directe - HAL - Université Paris Descartes, Apr 1, 2016
Le Centre pour la Communication Scientifique Directe - HAL - Inria, Sep 6, 2017
Optimization Letters, Mar 3, 2022
In this article the affiliation details for the below authors were published incorrectly.
Optimization Letters, 2022
Electronic Notes in Discrete Mathematics, 2015
The vehicle routing problem with multiple trips (V RP MT) is a variants of the standard (V RP), w... more The vehicle routing problem with multiple trips (V RP MT) is a variants of the standard (V RP), where each vehicle can be used more than once during the working period. For this NP-Hard problem, we propose a variable neighborhood search Algorithm in which four neighborhood structure are designed to find the planning of trips. The algorithm was tested over a set of benchmark problems and the obtained solutions were compared with five previously proposed algorithms. Encouraging results are obtained.
Electronic Notes in Discrete Mathematics, 2015
In this article, we consider a transportation problem with different kinds of locations: V , T , ... more In this article, we consider a transportation problem with different kinds of locations: V , T , and W. The set T ⊂ V consists of vertices that must be visited through the use of potential locations in V and W consists of locations that must be covered. The problem consists in minimizing vehicle routes on a subset of V including T. We develop a variable neighborhood search heuristic based on a variable neighborhood descent in which a set of locations must be visited, whereas another subset must be close enough to the planned routes. We tested and compared our algorithm on datasets based on TSP Library instances.
Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM), 2013
We propose a hybrid approach for multi-objective assignment problem which combines genetic algori... more We propose a hybrid approach for multi-objective assignment problem which combines genetic algorithm and mathematical programming techniques. This method is based on the dominance cost variant of the multi-objective genetic algorithm hybridized with exact method. The initial population is generated by solving a series of mono-objective assignment problems obtained by a suitable choice of a set of weights. The crossover operator solves a reduced mono-objective problem where the weights are chosen to identify an unexplored region. Numerical experiments show the efficiency of our approach.
Computers & Operations Research
The parking problem has become one of the major issues in urban transportation planning and traff... more The parking problem has become one of the major issues in urban transportation planning and traffic management research. The present paper deals with the dynamic assignment problem of the parking slots (places). The objectives are to provide a global satisfaction of all customers and maximize parking occupancy. A dynamic assignment problem consists in solving a sequence of assignment problems over time. To cope with all these aspects, we offer in this paper, a new approach based on a learning strategy: an Estimation of Distribution Algorithm (EDA) where a reinforcement learning method is used to support the assignment algorithm. We tested our approach with simulations for over 120 days, using a set of up to 10 parking lots (i.e. with up to 7,000 parking slots) and 13,000 requests distributed with different patterns over a day. The comparative study between an assignment algorithm with and without reinforcement learning algorithm has proven the relevance of our approach: the saving i...
Optimization Letters, Sep 27, 2014
In this paper we consider scheduling tasks on a multiprocessor system, taking into account commun... more In this paper we consider scheduling tasks on a multiprocessor system, taking into account communication delays. We propose a new Mixed Integer Program (MIP) formulation that drastically reduces both the number of variables and the number of constraints, when compared to the best mathematical programming formulations from the literature. In addition, we propose pre-processing procedures that generates cuts and bounds on all variables, reducing the solution space of the problem as well. Cuts are obtained by using forward and backward critical path method from project management field, while the upper bound is derived from the new greedy heuristic. Computational experience shows advantages of our approach.
The parking problem is nowadays one of the major issues in urban transportation planning and traf... more The parking problem is nowadays one of the major issues in urban transportation planning and traffic management research. In fact, the consequences of the lack of parking slots along with the inadequate management of these facilities are tremendous. The aim of this thesis is to provide efficient and robust algorithms in order to save time and money for drivers and to increase the income of parking managers. The problem is formulated as a multi-objective assignment problem in static and dynamic environments. First, for the static environment, we propose new two-phase heuristics to calculate an approximation of the set of efficient solutions for a bi-objective problem. In the first phase, we generate the supported efficient set with a standard dichotomic algorithm. In the second phase we use four metaheuristics to generate an approximation of the non-supported efficient solutions. The proposed approaches are tested on the bi-objective shortest path problem and the biobjective assignme...
Journal of Global Optimization