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《Computer Engineering and Design》 2007-11
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Greedy genetic algorithm for solving knapsack problems and its applications

HE Yi-chao~1 LIU Kun-qi~(1,2) ZHANG Cui-jun~1 ZHANG Wei~1 1.Department of Information Project,Shijiazhuang University of Economics,Shijiazhuang 050031,China; 2.School of Computer,China University of Geosciences,Wuhan 430074,China  
The flaw of greedy transform method adopted by hybrid henetic algorithm(HGA)is analyzed,which is a effective algorithm to solve knapsack problem in Ref.[2].A new define on greedy transform is redefined and a new and more effective implement method is advanced.The new method is combined with genetic algorithm to propose a new hybrid genetic algorithm that is greedy genetic algo- rithm(GGA).Using GGA,a best solution of famous knapsack sample is found in Ref.[2,4] at present.Moreover,for a knapsack sample in Ref.[7] and a randomly generated knapsack sample,the calculation results using GGA and HGA show that the global con- vergence of GGA is much more superior to HGA.
【Fund】: 河北省教育厅科研基金项目(2004454、2005338)。
【CateGory Index】: TP18
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