Estimation of Distribution Algorithms for Knapsack Problem

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...

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Bibliographic Details
Published in:Journal of software 2014-01, Vol.9 (1), p.104-104
Main Authors: Gao, Shang, Qiu, Ling, Cao, Cungen
Format: Article
Language:English
Subjects:
Algorithms
Combinatorial analysis
Computer programs
Computer simulation
Knapsack problem
Software
Statistics
Strategy
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Summary: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
ISSN:1796-217X
1796-217X
DOI:10.4304/jsw.9.1.104-110