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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.
Written for a wide readership, engineers, researchers, senior undergraduates and graduate students interested in the field of evolutionary algorithms and multiobjective optimization with some basic knowledge of evolutionary computation will find this book a useful addition to their book case.
Preface Introduction Review of MOEAs Conceptual Framework and Distribution Preservation Mechanisms for MOEAs Dynamic Population Size and Local Exploration for MOEAs A Distributed Cooperative Co-evolutionary Multiobjective Algorithm Learning the Search Range in Dynamic Environments Performance Assessment and Comparison of MOEAs A Multiobjective Evolutionary Algorithm Toolbox Evolutionary Computer-Aided Control System Design Evolutionary Design Automation for Multivariable QFT Control System Evolutionary Design of a HDD Control System Evolutionary Scheduling - VRPTW Evolutionary Scheduling - TTVRP Bibliography Index