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Mezmaz Mohand


Main Referenced Co-authors
Tuyttens, Daniel  (48)
Melab, Nouredine (34)
Fei, Hongying  (11)
Gmys, Jan  (10)
Jalwan, Jad  (8)
Main Referenced Keywords
Bayesian Optimization (1); Efficient Global Optimization (1); Evolutionary Algorithm (1); Massively Parallel Computing (1); Simulation (1);
Main Referenced Unit & Research Centers
CRTI - Centre de Recherche en Technologie de l'Information (15)
Main Referenced Disciplines
Mathematics (52)
Electrical & electronics engineering (8)
Computer science (5)
Mechanical engineering (3)

Publications (total 55)

The most downloaded
27 downloads
Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (19 February 2020). Towards Dynamic Selection of Evolution Controls in Parallel Bayesian Neural Network-assisted Genetic Algorithm. Paper presented at International Conference on Optimization and Learning OLA'2020 17-19 February, Cadiz, Spain. https://hdl.handle.net/20.500.12907/9658
The most cited
283 citations (Scopus®)
Mezmaz, M., Melab, N., Kessaci, Y., Lee, Y. C., Talbi, E.-G., Zomaya, A. Y., & Tuyttens, D. (01 November 2011). A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems. Journal of Parallel and Distributed Computing, 71 (11), 1497-1508. https://hdl.handle.net/20.500.12907/30061

Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (2021). Evolution Control Ensemble Models for Surrogate-Assisted Evolutionary Algorithms. In HPCS proceedings. IEEE.
Peer reviewed

Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (22 July 2020). Evolution Control for parallel ANN-assisted simulation-based optimization: Application to Tuberculosis Transmission Control. Future Generation Computer Systems, 113 (December 2020), 454-467. doi:10.1016/j.future.2020.07.005
Peer Reviewed verified by ORBi

Briffoteaux, G., Gobert, M., Ragonnet, R., Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). Parallel Surrogate-assisted Optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO. Swarm and Evolutionary Computation.
Peer Reviewed verified by ORBi

Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (19 February 2020). Towards Dynamic Selection of Evolution Controls in Parallel Bayesian Neural Network-assisted Genetic Algorithm. Paper presented at International Conference on Optimization and Learning OLA'2020 17-19 February, Cadiz, Spain.
Peer reviewed

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem. European Journal of Operational Research.
Peer Reviewed verified by ORBi

Melab, N., Gmys, J., Mezmaz, M., & Tuyttens, D. (16 June 2019). Many-core Branch-and-Bound for GPU accelerators and MIC coprocessors. Studies in Computational Intelligence, 833, 275-291.
Peer reviewed

Benmouna, Y., Mezmaz, M., Mahmoudi, S., & Chikh, M. A. (2019). Parallel cycle-based branch-and-bound method for Bayesian network learning. Pattern Analysis and Applications. doi:10.1007/s10044-019-00815-1
Peer Reviewed verified by ORBi

Briffoteaux, G., Melab, N., Mezmaz, M., & Tuyttens, D. (2018). An adaptive evolution control based on confident regions for surrogate-assisted optimization. In 2018 International Conference on High Performance Computing & Simulation, HPCS 2018, Orleans, France, July 16-20, 2018. IEEE. doi:10.1109/HPCS.2018.00130
Peer reviewed

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2018). Exactly solving permutation-based optimization problems on heterogeneous CPU/GPU clusters. Paper presented at OLA International Workshop on Optimization and Learning: Challenges and Applications, Alicante, Spain.

Melab, N., & Mezmaz, M. (10 May 2017). Multi and many-core computing for parallel metaheuristics [letter to the editor]. Concurrency and Computation: Practice and Experience, 29 (9). doi:10.1002/cpe.4116

Melab, N., Gmys, J., Mezmaz, M., & Tuyttens, D. (03 January 2017). Multi-core versus many-core computing for many-task Branch-and-Bound applied to big optimization problems. Future Generation Computer Systems, 82, 472-481.
Peer Reviewed verified by ORBi

Vaillant, G., Mezmaz, M., Tuyttens, D., & Melab, N. (2016). Vectorization of local search for solving flow-shop scheduling problem on Xeon PhiTM MIC co-processors. Paper presented at International Conference on High Performance Computing & Simulation, Innsbruck, Austria.

Kochetov, Y., Alekseeva, E., & Mezmaz, M. (20 October 2016). Local search heuristic for the discrete leader-follower problem with multiple follower objectives. AIP Conference Proceedings, 1776. doi:10.1063/1.4965328
Peer Reviewed verified by ORBi

Tuyttens, D., Mezmaz, M., Vaillant, G., & Melab, N. (05 July 2016). Exploring GRASP-based Metaheuristics to solve the Traveling Salesman Problem. Poster session presented at 28th European Conference on Operational Research, Poznan, Poland.

Tuyttens, D., Mezmaz, M., Vaillant, G., & Melab, N. (2016). Exploring GRASP-based Metaheuristics to solve the Traveling Salesman Problem. Paper presented at 28th European Conference on Operational Research, Poznan, Poland.

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (10 May 2016). IVM-Based parallel branch-and-bound using hierarchical work stealing on multi-GPU systems. Concurrency and Computation: Practice and Experience, 29 (9). doi:10.1002/cpe.4019
Peer Reviewed verified by ORBi

Alekseeva, E., Mezmaz, M., Tuyttens, D., & Melab, N. (10 May 2016). Parallel multi-core hyper-heuristic GRASP to solve permutation flow-shop problem. Concurrency and Computation: Practice and Experience, 29 (9). doi:10.1002/cpe.3835
Peer Reviewed verified by ORBi

Alekseeva, E., Bagein, M., Caucheteur, C., Kouroussis, G., Lobry, J., Manneback, P., Mezmaz, M., Moeyaert, V., Tuyttens, D., & Vanherck, T. (2016). INOGRAMS : un portefeuille de projets en vue d'un système global de gestion du rail.

Tuyttens, D., Mezmaz, M., & Alekseeva, E. (2016). Identification des paramètres du train. Polytech News, (53), 9.

Tuyttens, D., Mezmaz, M., & Godart, J.-M. (2016). GREENRAIL 2 : Optimisation multicritère des horaires de trains. Polytech News, (53), 7.

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (27 January 2016). A GPU-based Branch-and Bound algorithm using Integer-Vector-Matrix data structure. Parallel Computing, 59, 119-139. doi:10.1016/j.parco.2016.01.008
Peer Reviewed verified by ORBi

Gmys, J., Leroy, R., Mezmaz, M., Melab, N., & Tuyttens, D. (21 January 2016). Work stealing with private integer-vector-matrix data structure for multi-core branch-and-bound algorithms. Concurrency and Computation: Practice and Experience, 28 (18), 4463-4484. doi:10.1002/cpe.3771
Peer Reviewed verified by ORBi

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (20 January 2016). IVM-based Work Stealing for Parallel Branch-and-Bound on GPU. Lecture Notes in Computer Science, 9573, 548-558.
Peer reviewed

Melab, N., Leroy, R., Mezmaz, M., & Tuyttens, D. (2015). Parallel Branch-and-Bound using private IVM-based work stealing on Xeon Phi MIC coprocessor. Paper presented at International Conference on High Performance Computing & Simulation, Amsterdam, Netherlands.

Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2015). Towards a GPU-based branch-and-bound algorithm using an integer-vector-matrix data structure. Paper presented at ORBEL 29 - Belgian Conference on Operational Research, Antwerp, Belgium.

Mezmaz, M., Mehdi, M., Bouvry, P., Melab, N., Talbi, E.-G., & Tuyttens, D. (01 October 2014). Solving the three dimensional quadratic assignment problem on a computational grid. Cluster Computing, 17 (2), 205-217.
Peer Reviewed verified by ORBi

Mezmaz, M., Leroy, R., Melab, N., & Tuyttens, D. (2014). A multi-core parallel branch-and-bound algorithm using factorial number system. 28th IEEE International Parallel and Distributed Processing Symposium, 1203-1212.
Peer reviewed

Leroy, R., Mezmaz, M., Melab, N., & Tuyttens, D. (2014). Work stealing strategies for multi-core parallel branch-and-bound algorithm using factorial number system. Paper presented at PMAM 2014 - International Workshop on Programming Models and Applications for Multicores and Manycores, Orlando, United States - Florida.

Mezmaz, M., Vandaele, A., Tuyttens, D., Itani, S., & Melab, N. (2014). Towards a Lightning Inspired Meta-Heuristic. Paper presented at ORBEL 28, UMONS, Mons, Belgium.

Leroy, R., Mezmaz, M., Melab, N., & Tuyttens, D. (2014). Using factorial number system to solve permutation optimization problems. Paper presented at ORBEL 28, UMONS, Mons, Belgium.

Tuyttens, D., Godart, J.-M., Mezmaz, M., & Van Sevenant, M. (09 December 2013). Logistique ferroviaire : Optimiser la consommation électrique (Projets GreenRail I et II). Poster session presented at Lab'Insight, UMONS, FPMs, Belgium.

Tuyttens, D., Mezmaz, M., Godart, J.-M., & Van Sevenant, M. (12 March 2013). GreenRail : Economies d'énergie dans le transport ferroviaire. Poster session presented at Matinée des chercheurs (MDC 2013), Mons, Belgium.

Chakroun, I., Melab, N., Mezmaz, M., & Tuyttens, D. (01 January 2013). Combining multi-core and GPU computing for solving combinatorial optimization problems. Journal of Parallel and Distributed Computing, 73 (12), 1563-1577.
Peer Reviewed verified by ORBi

Chakroun, I., Mezmaz, M., Melab, N., & Bendjoudi, A. (01 January 2013). Reducing thread divergence in a GPU-accelerated branch-and-bound algorithm. Concurrency and Computation: Practice and Experience, 25 (8), 1121-1136.
Peer Reviewed verified by ORBi

Tuyttens, D., Fei, H., Mezmaz, M., & Jalwan, J. (01 January 2013). Simulation-based genetic algorithm towards an energy-efficient railway traffic control. Mathematical Problems in Engineering, 2013, 1-12.
Peer Reviewed verified by ORBi

Melab, N., Chakroun, I., Mezmaz, M., & Tuyttens, D. (2012). A GPU-accelerated Branch-and-Bound Algorithm for the Flow-Shop Scheduling Problem. Paper presented at IEEE International Conference on Cluster Computing, Beijing, China.

Mezmaz, M., Melab, N., & Tuyttens, D. (2012). A multi-threaded branch-and-bound algorithm for solving the flow-shop problem on a multi-core environment. In Large Scale Network-centric Computing Systems (pp. 53-70). Wiley-IEEE Computer Society Press.

Tuyttens, D., Fei, H., Mezmaz, M., & Jalwan, J. (30 November 2011). GREENRAIL : un rail plus vert ! Polytech News, 46.

Mezmaz, M., & Tuyttens, D. (30 November 2011). Ordonnancement moins énergivore de tâches dans les systèmes de calcul en nuage. Polytech News, 46.

Mezmaz, M., Melab, N., Kessaci, Y., Lee, Y. C., Talbi, E.-G., Zomaya, A. Y., & Tuyttens, D. (01 November 2011). A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems. Journal of Parallel and Distributed Computing, 71 (11), 1497-1508.
Peer Reviewed verified by ORBi

Kessaci, Y., Mezmaz, M., Melab, N., Talbi, E.-G., & Tuyttens, D. (23 June 2011). Parallel Evolutionary Algorithms for Energy Aware Scheduling. Studies in Computational Intelligence, 362, 75-100.
Peer reviewed

Tuyttens, D., Mezmaz, M., Fei, H., & Jalwan, J. (22 March 2011). Projet GreenRail. Poster session presented at 6ème édition de la Matinée des Chercheurs (MDC 2011), Mons, Belgium.

Mezmaz, M., Tuyttens, D., Jalwan, J., & Fei, H. (22 March 2011). GREENRAIL : Optimisation Energétique Ferroviaire. Paper presented at Troisième journée scientifique du Pôle Hainuyer, Ath, Belgium.

Fei, H., Tuyttens, D., Jalwan, J., & Mezmaz, M. (01 March 2011). Greenrail Energy Manager: Une Gestion Optimale du Trafic Ferroviaire. Recherche Opérationnelle et Transport Ferroviaire. Paper presented at 12e Congrès annuel de la Société française de Recherche Opérationnelle et d'Aide à la Décision, Saint-Etienne, France.

Fei, H., Tuyttens, D., Mezmaz, M., & Jalwan, J. (2011). An energy-conscious greedy heuristic to solve the train control problem. Paper presented at ORBEL 25, Gand, Belgium.

Mezmaz, M., Tuyttens, D., Fei, H., & Jalwan, J. (30 October 2010). Towards the State-of-the-Art of the Use of Genetic Algorithms to Solve Energy-Conscious Train Control Problem. Paper presented at International Conference on Metaheuristics and Nature Inspired Computing, Djerba Island, Tunisia.

Mezmaz, M., Kessaci, Y., Lee, Y. C., Melab, N., Talbi, E.-G., Zomaya, A. Y., & Tuyttens, D. (28 October 2010). A Parallel Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan Using Dynamic Voltage Scaling. Paper presented at International Conference on Metaheuristics and Nature Inspired Computing, Djerba Island, Tunisia.

Mezmaz, M., Kessaci, Y., Lee, Y. C., Melab, N., Talbi, E.-G., Zomaya, A. Y., & Tuyttens, D. (2010). A Parallel Island-based Hybrid Genetic Algorithm for Precedence-constrained Applications to Minimize Energy Consumption and Makespan. Proceedings - IEEE/ACM International Workshop on Grid Computing 2010, Article number 5697985, Pages 274-281 2010 11th IEEE/ACM International Conference on Grid Computing, 274-281.
Peer reviewed

Fei, H., Tuyttens, D., Mezmaz, M., & Jalwan, J. (01 September 2010). The state-of-art about energy-efficient railway traffic control. Paper presented at International Conference Operations Research, Munich, Germany.

Mezmaz, M., Lee, Y. C., Melab, N., Talbi, E.-G., & Zomaya, A. Y. (2010). A Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan for Precedence-constrained Applications Using Dynamic Voltage Scaling. Paper presented at IEEE Congress on Evolutionary Computation (IEEE CEC 2010) in conjunction with IEEE WCCI 2010, Barcelone, Spain.

Tuyttens, D., Mezmaz, M., Jalwan, J., & Fei, H. (07 May 2010). Le projet GREENRAIL : Recherches en optimisation. Paper presented at Seconde journée scientifique du Pöle Hainuyer, Mons, Belgium.

Tuyttens, D., Fei, H., Mezmaz, M., & Jalwan, J. (04 March 2010). GreenRail : un rail moins énergivore. Polytech.News, 43.

Mezmaz, M. (23 February 2010). Nouvelles approches pour le passage sur grilles de calcul de méthodes d'optimisation combinatoire. Paper presented at Midis de MathRO, .

Mezmaz, M., Fei, H., Jalwan, J., & Tuyttens, D. (11 February 2010). GreenRail : vers un système ferroviaire moins énergivore. Paper presented at Midis de MathRO, .

Mezmaz, M. (2010). Methodes d'Optimisation Combinatoire sur Grilles de Calcul : Une approche efficace pour le passage sur grilles de calcul de méthodes d'optimisation combinatoire. Editions universitaires europeennes.

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