DocumentCode :
459045
Title :
Interactive Genetic Algorithms for Optimization of Problems with Multiple Modes and Implicit Performance Indices
Author :
Gong, Dunwei ; Yuan, Jie
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou
Volume :
2
fYear :
2006
fDate :
16-18 Oct. 2006
Firstpage :
1001
Lastpage :
1005
Abstract :
Optimization of problems with multiple modes and implicit performance indices is common, but so far there´s still no effective method to solve it. An interactive genetic algorithm (IGA) for optimizing such problems is presented in this paper Firstly, according to the distribution and the fitness of individuals in an evolutionary population, the property in multiple modes and the number of modes of an optimized problem is determined, and the optimal individuals of all modes are conserved. Then a user assigns the fitness to offspring obtained by evolving one generation referring to the phenotypes and the fitness of these reserved optimal individuals. The algorithm is applied to fashion design and the experimental results validate its efficiency. The achievement of the paper provides a feasible approach to looking for several optimal solutions of an optimized problem with multiple modes and implicit performance indices
Keywords :
design; genetic algorithms; fashion design; interactive genetic algorithms; phenotypes; problem optimization; Acceleration; Algorithm design and analysis; Convergence; Fatigue; Genetic algorithms; Humans; Investments; Neural networks; Optimization methods; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
Type :
conf
DOI :
10.1109/ISDA.2006.253748
Filename :
4021800
Link To Document :
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