Multi-Objective Optimization Using Evolutionary Algorithms By Kalyanmoy Deb, Deb Kalyanmoy
2001 | 518 Pages | ISBN: 047187339X | PDF | 33 MB
2001 | 518 Pages | ISBN: 047187339X | PDF | 33 MB
Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run.
- 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
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