Multi-Objective Optimization using Evolutionary Algorithms
- Comprehensive coverage of this growing area of research
- Carefully introduces each algorithm with examples and in-depth discussion
- Includes many applications to real-world problems, including engineering design and scheduling
- Includes discussion of advanced topics and future research
- Can be used as a course text or for self-study
- Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms
The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Non-Elitist Multi-Objective Evolutionary Algorithms.
Elitist Multi-Objective Evolutionary Algorithms.
Constrained Multi-Objective Evolutionary Algorithms.
Salient Issues of Multi-Objective Evolutionary Algorithms.
Applications of Multi-Objective Evolutionary Algorithms.
"...discusses two multi-objective optimization procedures, namely the ideal procedure and the preference-based one." (Zentralblatt MATH, Vol. 970, 2001/20)
Excerpt from Preface: "...provides an extensive discussion on the principles of multi-objective optimization and on a number of classical approaches." (Mathematical Reviews, 2002)
"...As a survey, this book is exemplary and forms an essential resource for EMO researchers at the present time." (Siam Review, Vol.44, No.3, 2002)
"...a readable account of a topic of current interest in operational research." (Mathematika, No.48, 2001)
an outstandingly well-organized and clearly written account of the subject (The Mathematical Gazette, July 2003)