Aim and scope:Solving many-objective optimization problems (MaOPs) has drawn increasing attention in the research community due to the fact that MaOPs cannot be solved efficiently using traditional MOEAs developed for solving multi-objective optimization problems with two or three objectives. Among various ideas adopted for many-objective optimization, one big challenge is to develop highly efficient and effective non-dominated sorting methods and Pareto-based multi-objective evolutionary algorithms (MOEAs) for MaOPs. The aim of this special session is to bring together researchers in the evolutionary computation community dedicated to solving MaOPs using non-dominated sorting and Pareto-based approaches to MaOPs. Topics of the special session include, but are not limited to
- Reducing the computational cost of non-dominated sorting for MaOPs
- New Pareto dominance relationships for MOEAs to solve MaOPs
- New convergence/diversity-related metrics combined with dominance comparison for MaOPs
- Efficient Pareto-based MOEAs for large scale multi-objective optimization problems
- Real world applications of efficient non-dominated sorting and/or Pareto-based MOEAs for MaOPs
Organizers:Xingyi Zhang, School of Computer Science and Technology, Anhui University, China email@example.com
Ran Cheng, Department of Computer Science, University of Surrey, UK. firstname.lastname@example.org
Yaochu Jin, Department of Computer Science, University of Surrey, UK. email@example.com
Xingyi Zhang received the B.Sc. from Fuyang Normal College in 2003, and the M.Sc. in 2006and Ph.D. in 2009 both from Huazhong University of Science and Technology. Currently, he is an Associate Professor in the School of Computer Science and Technology, Anhui University. His main research interests include unconventional models and algorithms of computation, multi-objective optimization and membrane computing. He has published several papers on many-objective optimization evolutionary algorithms to reduce computational cost of non-dominated sorting and improve the performance of Pareto-based MOEAs for MaOPs.
 Xingyi Zhang, Ye Tian, Ran Cheng, Yaochu Jin. An efficient approach to non-dominated sorting for evolutionary multi-objective optimization. IEEE Transactions on Evolutionary Computation, 2015, 19(2): 201-213.
 Xingyi Zhang, Ye Tian, Yaochu Jin. A knee point driven evolutionary algorithm for many-objective optimization. IEEE Transactions on Evolutionary Computation, 2014, dol.10.1109/TEVC.2014.2378512
Ran Cheng received the B.Sc. degree from Northeastern University, Shenyang, China, in 2010. He is currently working toward the Ph.D. degree from the Department of Computer Science, University of Surrey, Guildford, Surrey, U.K. His research interests include multi/many-objective optimization, estimation of distribution algorithms, and swarm intelligence.
 Ran Cheng , Yaochu Jin, Kaname Narukawa and Bernhard Sendhoff. A Multiobjective Evolutionary Algorithm using Gaussian Process based Inverse Modeling. IEEE Transactions on Evolutionary Computation, 2015 (accepted)
 Ran Cheng and Yaochu Jin. A Competitive Swarm Optimizer for Large Scale Optimization. IEEE Transactions on Cybernetics, 45(2): 191-204, 2015
 Ran Cheng and Yaochu Jin. A Social Learning Particle Swarm Optimization Algorithm for Scalable Optimization. Information Sciences, 291: 43-60, 2015
Yaochu Jin is currently a Professor and a Chair of Computational Intelligence with the Department of Computing, University of Surrey, Guildford, U.K., where he is also the Head of the Nature Inspired Computing and Engineering Group. He is also a Finland Distinguished Professor, Finland, and a Changjiang Distinguished Visiting Professor, China.
Dr. Jin is an Associate Editor of the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Cybernetics, the IEEE Transactions on Autonomous Mental Development, the IEEE Transactions on Nanobiosciences, the IEEE Computational Intelligence Magazine, Evolutionary Computation (MIT), BioSystems (Elsevier), and Soft Computing (Springer). He is currently an IEEE Distinguished Lecturer and Vice President for Technical Activities of the IEEE Computational Intelligence Society. He was the recipient of the 2014 IEEE Computational Intelligence Magazine Outstanding Paper Award and the Best Paper Award of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.