Department of Electronic Engineering, National Kaohsiung University of Applied Sciences

公告消息, 最新消息(News)

9五月

EVOLUTIONARY COMPUTATION AND MULTIOBJECTIVE OPTIMIZATION

EVOLUTIONARY COMPUTATION AND MULTIOBJECTIVE OPTIMIZATION

 

Instructor:                              Regents Professor Gary G. Yen, FIEEE, FIET

Oklahoma State University

School of Electrical and Computer Engineering

http://isc.okstate.edu/

+1-405-744-7743, gyen@okstate.edu

 

Reference Books:                  Genetic Algorithms in Search, Optimization & Machine Learning

Goldberg, Addison-Wesley, 1989

An Introduction to Genetic Algorithms

Mitchell, MIT, 1996

Ant Colony Optimization

Dorigo and Stutzle, MIT, 2004

Multi-Objective Optimization Using Evolutionary Algorithms

Deb, John Wiley, 2001

 

Objectives:                              Evolutionary computation is the study of biologically motivated computational paradigms which exert novel ideas and inspiration from natural evolution and adaptation. The applications of population-based heuristics in solving multiobjective optimization problems have been receiving a growing attention. To search for a family of Pareto optimal solutions based on nature-inspiring problem solving paradigms, Evolutionary Multiobjective Optimization Algorithms have been successfully exploited to solve optimization problems in which the fitness measures and even constraints are uncertain and changed over time.

 

In this short course, I will present a survey of emerging biologically motivated computational paradigms and hand-on working knowledge with specific application domains. The lectures should provide a complete and balance view of this growing topic, evolutionary multiobjective optimization. Topics include, but not limited to,

  • computational intelligence;
  • simulated annealing;
  • evolutionary computation;
  • ant colony system;
  • particle swarm intelligence;
  • genetic algorihms (search operators, search schemes, niching, constraint handling);
  • evolutionary multiobjective optimization;
  • co-evolution;
  • artificial immune system;
  • memetic algorithm;

Biography

Gary G. Yen received the Ph.D. degree in electrical and computer engineering from the University of Notre Dame in 1992. He is currently a Regents Professor in the School of Electrical and Computer Engineering, Oklahoma State University. His research is supported by the DoD, DoE, EPA, NASA, NSF, and Process Industry. His research interest includes intelligent control, computational intelligence, evolutionary multiobjective optimization, conditional health monitoring, signal processing and their industrial/defense applications.

 

Gary was an associate editor of the IEEE Transactions on Neural Networks and IEEE Control Systems Magazine during 1994-1999, and of the IEEE Transactions on Control Systems Technology, IEEE Transactions on Systems, Man and Cybernetics and IFAC Journal on Automatica and Mechatronics during 2000-2010. He is currently serving as an associate editor for the IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics and International Journal of Swarm Intelligence Research. Gary served as Vice President for the Technical Activities, IEEE Computational Intelligence Society in 2004-2005 and is the founding editor-in-chief of the IEEE Computational Intelligence Magazine, 2006-2009. He was the President of the IEEE Computational Intelligence Society in 2010-2011 and is elected as a Distinguished Lecturer. He received Regents Distinguished Research Award from OSU in 2009 and 2011 Andrew P Sage Best Transactions Paper award from IEEE Systems, Man and Cybernetics Society. He holds honorary professorship from Northeast University, Sichuan University and Dalian University of Technology in China. He chaired the Award Committee in 2014-2015 and currently chair Fellow Committee of the IEEE Computational Intelligence Society. He is a Fellow of IEEE and IET.