DocumentCode :
1752876
Title :
An Improved Variable-Length Representation Approach for Knapsack Problem
Author :
Yi, Xu ; Xinjie, Yu
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
3446
Lastpage :
3450
Abstract :
One of the methods to solve knapsack problem is the variable-length representation approach based on genetic algorithm (GA). The original variable-length representation approach has the problem of low efficiency. In this paper we present a improved approach. In the early stage of the evolution, the heuristic searching method is applied to search better solutions rapidly, and in the latter part of evolution the random searching method is applied to improve the result. Through the simulation on some benchmark and two random knapsack problems, the results show that the improved variable-length representation approach has superiority in speed and accuracy over the standard method
Keywords :
genetic algorithms; knapsack problems; search problems; genetic algorithm; heuristic searching; knapsack problem; random searching; variable-length representation; Automation; Genetics; Intelligent control; Power systems; Genetic Algorithm(GA); Heuristic Method; Knapsack Problem; Variable-length Representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713008
Filename :
1713008
Link To Document :
بازگشت