Interactive Genetic Algorithm Principles and Applications

Author: Gong Dunwei
Publisher:
Publish Date: 2007-01-01
Features: Interactive genetic algorithms (IGAs) are intelligent computing methods for solving implicit performance indicator optimization problems, and they have been successfully applied in many fields in recent years. This book aims to elaborate on the principles and applications of interactive genetic algorithms, with the main content including: an overview of interactive genetic algorithms, the volatility of the interactive genetic algorithm environment and the inconsistency of the fitness of evolving individuals, an abstract model of interactive genetic algorithms based on relational algebra, the problem of human fatigue in single-population interactive genetic algorithms and various effective solutions, multi-population collaborative interactive genetic algorithms, noise models and fitness adjustment strategies for interactive genetic algorithms, and the application of interactive genetic algorithms in hybrid indicator optimization problems. While providing a detailed explanation of the theory and methods of interactive genetic algorithms, this book also presents its application in a clothing evolutionary design system. This book is a crystallization of the author's series of research achievements on interactive genetic algorithms supported by the National Natural Science Foundation of China in recent years. It is suitable for teachers and graduate students of relevant majors in science and engineering universities, as well as researchers in the fields of natural sciences and engineering technology.