DocumentCode :
2052583
Title :
Hybrid genetic algorithm for solving Knapsack problem
Author :
Tharanipriya, P.G. ; Vishnuraja, P.
Author_Institution :
Kongu Eng. Coll., Perundurai, India
fYear :
2013
fDate :
21-22 Feb. 2013
Firstpage :
416
Lastpage :
420
Abstract :
In clustering, clustering techniques are applied to get the best solution. The traditional clustering algorithms lead to local optimum. Hybrid genetic algorithm which includes multi clustering genetic algorithm with rough set theory is to be proposed to improve the efficiency and to get the optimal solution. The selection procedure of genetic algorithm has lower efficiency. So rough set theory can be used for selecting chromosomes for further process which is applied in 0-1 Knapsack problem.
Keywords :
data mining; genetic algorithms; knapsack problems; pattern clustering; rough set theory; 0-1 knapsack problem; clustering techniques; data mining; hybrid genetic algorithm; multi clustering genetic algorithm; rough set theory; Algorithm design and analysis; Clustering algorithms; Data mining; Evolution (biology); Genetic algorithms; Optimization; Set theory; Genetic Algorithm; Knapsack problem; Multi-clustering genetic algorithm; Rough set Theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2013 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4673-5786-9
Type :
conf
DOI :
10.1109/ICICES.2013.6508280
Filename :
6508280
Link To Document :
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