Institute
FSEG-NABEUL
Country: Tunisia
Institute type: University
FEMISE Institute: not sure
Areas research expertise
- Other
Computer Science and Decision Making
Participation in FEMISE-funded research: %s
Last publications
Slim Bechikh, Rituparna Datta, Abhishek Gupta, “Recent Advances in Evolutionary Multi-objective Optimization”, Adaptation, Learning, and Optimization (ISBN: 978-3-319-42978-6), Springer, 2017.
Abir Chaabani, Slim Bechikh, Lamjed Ben Said, “A New Co-evolutionary Decomposition-based Algorithm for Bi-level Combinatorial Optimization”, Applied Intelligence, accepted (DOI: 10.1007/s10489-017-1115-9), 2018.
Radhia Azzouz, Slim Bechikh, Lamjed Ben Said, Walid Trabelsi, “Handling Time-Varying Constraints and Objectives in Dynamic Evolutionary Multi-objective Optimization”, Swarm and Evolutionary Computation, accepted (DOI: 10.1016/j.swevo.2017.10.005), 2017.
Maha Elarbi, Slim Bechikh, Abhishek Gupta, Lamjed Ben Said, Yew-Soon Ong, “A New Decomposition-based NSGA-II for Many-objective Optimization”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, accepted (DOI: 10.1109/TSMC.2017.2654301), 2017.
Radhia Azzouz, Slim Bechikh, Lamjed Ben Said, “A Dynamic Multi-objective Evolutionary Algorithm using a Change Severity-based Adaptive Population Management Strategy”, Soft Computing – A Fusion of Foundations, Methodologies, and Applications, vol. 21, no. 4, pp. 885–906, 2017.
Slim Bechikh, Abir Chaabani, Lamjed Ben Said, “An Efficient Chemical Reaction Optimization Algorithm for Multi-objective Optimization”, IEEE Transactions on Cybernetics, vol. 45, no. 10, pp. 2051–2064, 2015.
Meriem Bousselmi, Slim Bechikh, Chih-Cheng Hung, Lamjed Ben Said, “Bi-MOCK: A Multi-objective Evolutionary Algorithm for Bi-clustering with Automatic Determination of the Number of Bi-clusters”, in Proc. 24th International Conference on Neural Information Processing (ICONIP'17), accepted, Springer, Guangzhou, China, 2017.
Maha Elarbi, Slim Bechikh, Lamjed Ben Said, “On the Importance of Isolated Solutions in Constrained Decomposition-based Many-objective Optimization”, in Proc. Genetic and Evolutionary Computation Conference (GECCO'17), pp. 561–568, ACM Press, Berlin, Germany, 2017.