Evolutionary multiobjective optimization is currently gaining a lot of attention, particularly for researchers in the evolutionary computation communities. This monograph is suitable as a secondary text for graduate level computational intelligence courses, and as a reference for researchers, lecturers, and practitioners in industry.

Evolutionary Multi Objective is an important area which is presently gaining considerable attention. There is a lack of books in the area. The book will be recommended for the authors' two computational intelligence courses (often with a total of over 150 students)

Inhalt
Review of MOEAs.- Conceptual Framework and Distribution Preservation Mechanisms for MOEAs.- Decision Supports and Advanced Features for MOEAs.- Dynamic Population Size and Local Exploration for MOEAs.- A Distributed Cooperative Coevolutionary 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 of Multivariable QFT Control System.- Evolutionary Design of HDD Servo Control System.- Evolutionary Scheduling VRPTW.- Evolutionary Scheduling TTVRP.