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.This chapter presents an optimization toolbox that is built upon the MOEA algorithm (Tan et al. 1 999b) as described in Chapter 4. The MOEA toolbox is ready for immediate use with minimal knowledge needed in Matlab or evolutionary computing. ... to the Matlab environment; (5) it is capable of generating optimized code for embedded systems, rapid prototyping, and hardware-in-the-loop design.
Title | : | Multiobjective Evolutionary Algorithms and Applications |
Author | : | Kay Chen Tan, Eik Fun Khor, T. H. Lee, Tong Heng Lee |
Publisher | : | Springer Science & Business Media - 2005-05-04 |
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