Evolutionary Multiobjective Optimization

Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.

Zusammenfassung

Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts.

Important features include:

• Detailed overview of all the multiobjective optimization paradigms using evolutionary algorithms
• Excellent coverage of timely, advanced multiobjective optimization topics
• State-of-the-art theoretical research and application developments

• Chapters authored by pioneers in the field
  Academics and industrial scientists as well as engineers engaged in research, development and application of evolutionary algorithm based Multiobjective Optimization will find the comprehensive coverage of this book invaluable.

  Inhalt
  Evolutionary Multiobjective Optimization.- Recent Trends in Evolutionary Multiobjective Optimization.- Self-adaptation and Convergence of Multiobjective Evolutionary Algorithms in Continuous Search Spaces.- A Simple Approach to Evolutionary Multiobjective Optimization.- Quad-trees: A Data Structure for Storing Pareto Sets in Multiobjective Evolutionary Algorithms with Elitism.- Scalable Test Problems for Evolutionary Multiobjective Optimization.- Particle Swarm Inspired Evolutionary Algorithm (PS-EA) for Multi-Criteria Optimization Problems.- Evolving Continuous Pareto Regions.- MOGADES: Multi-Objective Genetic Algorithm with Distributed Environment Scheme.- Use of Multiobjective Optimization Concepts to Handle Constraints in Genetic Algorithms.- Multi-criteria Optimization of Finite State Automata: Maximizing Performance while Minimizing Description Length.- Multiobjective Optimization of Space Structures under Static and Seismic Loading Conditions.