This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.
We would like to thank Dr. Janusz Kacprzyk for inviting us to edit this book in the
Springer book series “Studies in Computational Intelligence”. We acknowledge
the contributors for their fine work and cooperation during the book preparation ...
AI '93 and AI '94 Workshops on Evolutionary Computation, Melbourne, Victoria, Australia, November 16, 1993, Armidale, NSW, Australia, November 21-22, 1994. Selected Papers
This volume contains the best carefully revised full papers selected from the presentations accepted for the AI '93 and AI '94 Workshop on Evolutionary Computation held in Australia. The 21 papers included cover a wide range of topics in the field of evolutionary computation, from constrained function optimization to combinatorial optimization, from evolutionary programming to genetic programming, from robotic strategy learning to co-evolutionary game strategy learning. The papers reflect important recent progress in the field; more than half of the papers come from overseas.
AI '93 and AI '94 Workshops on Evolutionary Computation, Melbourne, Victoria,
Australia, November 16, 1993, Armidale, NSW, Australia, November 21-22, 1994.
Selected Papers Xin Yao ...
Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting.
Some of the terminologies used in evolutionary computation have been
borrowed from these fields to reflect their connections, such as genetic algorithms
, genotypes, phenotypes, species, etc. Although the research in evolutionary ...
