期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2010
卷号：1
期号：4
DOI：10.14569/IJACSA.2010.010411
出版社：Science and Information Society (SAI)
摘要：Problems with multiple objectives can be solved by using Pareto optimization techniques in evolutionary multi-objective optimization algorithms. Many applications involve multiple objective functions and the Pareto front may contain a very large number of points. Selecting a solution from such a large set is potentially intractable for a decision maker. Previous approaches to this problem aimed to find a representative subset of the solution set. Clustering techniques can be used to organize and classify the solutions. Implementation of this methodology for various applications and in a decision support system is also discussed.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Multiobjective;Pareto front ;Clustering techniques
