Evolutionary Algorithms

Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required.

Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems.

Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms. It covers such hot topics as: • genetic algorithms, • differential evolution, • swarm intelligence, and • artificial immune systems.

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an area of active research. In general, data mining consists of extracting knowledge from data. In this book we particularly emphasize the importance of discovering comprehensible and interesting knowledge, which is potentially useful to the reader for intelligent decision making.

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an area of active research. In general, data mining consists of extracting knowledge from data. In this book we particularly emphasize the importance of discovering comprehensible and interesting knowledge, which is potentially useful to the reader for intelligent decision making.

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an area of active research. In general, data mining consists of extracting knowledge from data. In this book we particularly emphasize the importance of discovering comprehensible and interesting knowledge, which is potentially useful to the reader for intelligent decision making.