¹School of Computer Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212003, China
²Artificial Intelligence of Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong 643000,China
³Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China

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Abstract—Estimation of distribution algorithms ( EDAs ) is a new kind of evolution algorithm. In EDAs , through the statistics of the information of selected individuals in current group, the probability of the individual distribution in next generation is given and the next generation of group is formed by random sampling. A wide range of mathematical model of the knapsack problem are proposed. In this paper, the EDAs is applied to solve the knapsack problem. The influence of several strategies, such as numbers of population and better population selection proportions are analyzed. Simulation results show that the EDAs is reliable and effective for solving the knapsack problem. The Maltab code is given also. It can easily be modified for any combinatorial problem for which we have no good specialized algorithm.

Index Terms—estimation distribution algorithm, knapsack problem, genetic algorithm

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Cite: Shang Gao, Ling Qiu, Cungen Cao, "Estimation of Distribution Algorithms for Knapsack Problem," Journal of Software vol. 9, no. 1, pp. 104-110, 2014.