Particle dynamical evolutionary algorithms are getting increasingly popular due to their capabilities in dealing with real world problems, which are complicated in complexity and data volume. This book aims to present the theoretical and methodological studies on particle dynamical evolutionary algorithms as well as their various applications to many real world problems from science, technology and commerce. It is comprised of seven chapters including an introductory chapter giving the development trend, current status and basic concepts of evolutionary computation (EC). The chapters are selected on the basis of fundamental ideas and concepts rather than the thoroughness of techniques deployed, such as the particle transportation theory, the principle of energy minimization, and the law of entropy increasing; new dynamical evolutionary algorithms based on the particle transportation theory; hybrid evolutionary algorithms for solving optimization problems; multi-objective dynamical evolutionary algorithms based on the transportation theory; and novel algorithms for evolving encryption sequences based on particle dynamics.
Dr. Kangshun Li is currently a vice chairman of IEEE Guangzhou Computational Intelligence Society, a senior member of IEEE and a full professor at South China Agricultural University (SCAU), Guangzhou, China. He holds the dean position in School of Information at SCAU. He has published over 107 papers in peer-reviewed journals and conferences.