By Carlos A Coello Coello, Gary B Lamont
This booklet provides an in depth number of multi-objective difficulties throughout varied disciplines, in addition to statistical recommendations utilizing multi-objective evolutionary algorithms (MOEAs). the themes mentioned serve to advertise a much broader realizing in addition to using MOEAs, the purpose being to discover strong suggestions for high-dimensional real-world layout functions. The publication encompasses a huge choice of MOEA functions from many researchers, and therefore offers the practitioner with special algorithmic path to accomplish reliable leads to their chosen challenge area.
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Extra resources for Applications Of Multi-Objective Evolutionary Algorithms (Advances in Natural Computation)
The use of EAs for optimization tasks has become very popular in the last few years, spanning virtually every application domain 22 ' 44 ' 25 ' 4 . From the several emergent research areas in which EAs have become in1 2 Carlos A. Coello Coello and Gary B. Lamont creasingly popular, multi-objective optimization has had one of the fastest growing in recent years12. A multi-objective optimization problem (MOP) differs from a single-objective optimization problem because it contains several objectives that require optimization.
Springer-Verlag. Lecture Notes in Computer Science No. 1993, 2001. 42. Gisele L. Pappa, Alex A. A. Kaestner. Attribute Selection with a Multiobjective Genetic Algorithm. In G. L. Ramalho, editors, Proceedings of the 16th Brazilian Symposium on Artificial Intelligence (SBIA-2002), pages 280-290. Springer-Verlag. Lecture Notes in Artificial Intelligence Vol. 2507, 2002. 43. Gisele L. Pappa, Alex A. Freitas, and Celso A. A. Kaestner. A Multiobjective Genetic Algorithm for Attribute Selection. In Proceedings of the 4th International Conference on Recent Advances in Soft Computing (RASC-2002), pages 116-121, Nottingham, UK, December 2002.
Springer. Lecture Notes in Economics and Mathematical Systems Vol. 535. 62. Eckart Zitzler, Marco Laumanns, and Lothar Thiele.
Applications Of Multi-Objective Evolutionary Algorithms (Advances in Natural Computation) by Carlos A Coello Coello, Gary B Lamont