Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2548
Adaptive genetic algorithm and quasiparallel genetic algorithm: application to knapsack problem
Authors 
Szeto, KY
Zhang, J. 


Issue Date  2006  
Source  Lecture Notes in Computer Science , v. 3743, 2006, p. 189196  
Summary  A new adaptive genetic algorithm using mutation matrix is introduced and implemented in a single computer using the quasiparallel time sharing algorithm for the solution of the zero/one knapsack problem. The mutation matrix M(t) is constructed using the locus statistics and the fitness distribution in a population A(t) with N rows and L columns, where N is the size of the population and L is the length of the encoded chromosomes. The mutation matrix is parameter free and adaptive as it is time dependent and captures the accumulated information in the past generation. Two strategies of evolution, mutation by row (chromosome), and mutation by column (locus) are discussed. Time sharing experiment on these two strategies is performed on a single computer for solving the knapsack problem. Based on the investment frontier of time allocation, the optimal configuration for solving the knapsack problem is found.  
Subjects  
ISSN  03029743  
Rights  The original publication is available at http://www.springerlink.com/. Please use the appropriate URL and/or DOI for the article. The access script to link to it is: http://library.ust.hk/cgi/db/doi.pl?10.1007/11666806_20  
Language  English 

Format  Article  
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