Optimization on a multimodal objective landscape has long become an important and challenging problem in computer science and operations research. Evolutionary computation (EC) has become a fundamental technique for complex optimization. As a special type of EC algorithms, Estimation of Distribution Algorithm (EDA) works by constructing a probability model to estimate the distribution of the predominant individuals in the population. With this probability distribution based search behavior, EDA is good at maintaining search diversity, and is applicable in both continuous and discrete search space.
Motivated by the idea of EDA, this talk introduces two frameworks of probability distribution based evolutionary algorithms (EAs). The first framework presents a method to combine probability-based evolutionary operators with the niching strategy, so that higher search diversity can be maintained. As a result, the algorithms under this framework further improve search diversity of EAs and can be applied to find multiple globally optimal solutions. In particular, two algorithms under this framework will be presented: multimodal EDA (MEDA) and multimodal adaptive ant colony optimization (MA-ACO). The second framework aims at extending the applicability of EAs on both continuous and discrete space. Since some popular EAs are originally defined on continuous real vector space and they cannot be directly used to solve discrete optimization problems, this framework introduces the idea probability distribution based evolution and redefines their evolutionary operators on discrete set space. As a result, the applicability of these algorithms can be significantly improved.
Wei-Neng Chen received a Bachelor's degree and a Ph.D. degree from Sun Yat-sen University, China, in 2006 and 2012, respectively. He is currently a professor with the School of Computer Science and Engineering, South China University of Technology, China. His current research interests include swarm intelligence algorithms and their applications on cloud computing, operations research and software engineering. Dr. Chen has published 60 papers in international journals and conferences. His doctoral thesis received the IEEE Computational Intelligence Society (CIS) Outstanding Dissertation Award in 2016. He also received the National Science Fund for Excellent Young Scholars in 2016.
Last modified: Monday, 30-Jan-2017 10:42:14 NZDT
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