计算机科学 ›› 2011, Vol. 38 ›› Issue (7): 225-227.
• 人工智能 • 上一篇 下一篇
周雅兰,朱耀辉,张军
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ZHOU Ya-lan,ZHU Yao-hui,ZHANG Jun
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摘要： 如何将差分演化算法应用于离散领域是目前该领域的一个热点研究问题。用分布佑计算法对搜索空间中优质解的分布进行建模，然后根据建立的模型抽样产生新解，利用分布佑计这种全局信息学习的机制，提出具有学习机制的离散差分演化算法并用于求解多维背包问题。实验结果表明，提出的算法具有良好的性能。
关键词: 离散差分演化算法，学习机制，分布估计算法，多维背包问题
Abstract: How to apply differential evolution to discrete field is currently a hot research problem in this area. Estimation of distribution algorithms build a probability model which characterizes the distribution of the current promising solutions in the search space and generates new solutions according to the model. Using the global learning of estimation of distribution algorithms, a discrete differential evolution with learning mechanism was proposed for multidimensional knack problem. Simulation results show that the proposed algorithm has good performance.
Key words: Discrete differential evolution,Learning mechanism, Estimation of distribution algorithm, Multidimensional knack problem
周雅兰,朱耀辉,张军. 具有学习机制的离散差分演化算法[J]. 计算机科学, 2011, 38(7): 225-227. https://doi.org/
ZHOU Ya-lan,ZHU Yao-hui,ZHANG Jun. Discrete Differential Evolution with Learning Mechanism[J]. Computer Science, 2011, 38(7): 225-227. https://doi.org/
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