DocumentCode :
441938
Title :
A partheno-genetic algorithm for multidimensional knapsack problem
Author :
Bai, Jian-Cong ; Chang, Hui-you ; Yi, Yang
Author_Institution :
Dept. of Comput. Sci., Zhongshan Univ., GuangZhou, China
Volume :
5
fYear :
2005
fDate :
18-21 Aug. 2005
Firstpage :
2962
Abstract :
The multidimensional knapsack problem is one of the most well known integer programming problems and applied in resource allocation widely. This paper proposes a partheno-genetic algorithm (PGA) for solving this problem. The PGA repeals crossover operators and implements the functions of crossover and mutation by partheno-genetic operators. In partheno-genetic operation, new heuristics and a worst-removed operator are designed for improving the profit of the solution. Simulation results show that the PGA achieves good performance, and it can restraints the immature convergence phenomenon efficiently and the worst-removed operator can improve the searching ability.
Keywords :
genetic algorithms; integer programming; knapsack problems; crossover operator; integer programming; multidimensional knapsack problem; partheno-genetic algorithm; resource allocation; worst-removed operator; Computer science; Electronic mail; Electronics packaging; Genetic algorithms; Genetic mutations; Heuristic algorithms; Linear programming; Multidimensional systems; Partial response channels; Resource management; Partheno-genetic operator; multidimensional knapsack problem; worst-removed operator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
Type :
conf
DOI :
10.1109/ICMLC.2005.1527449
Filename :
1527449
Link To Document :
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