| 一种维持种群多样性的多目标差分演化算法 |
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| 引用本文： | 敖友云,李枫. 一种维持种群多样性的多目标差分演化算法[J]. 计算机工程与科学, 2008, 30(12): 75-78 |
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| 作者姓名： | 敖友云 李枫 |
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| 作者单位： | 安庆师范学院计算机与信息学院,安徽,安庆,246011;上海师范大学数理信息学院,上海,200234 |
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| 摘 要： | 差分演化算法是一种简单而有效的全局优化算法。本文将差分演化算法用于求解多目标优化问题，给出了一种维持种群多样性的多目标差分演化算法。该算法采用正交设计法初始化种群，改进差分演化算子，从而有利于维持种群多样性，提高演化算法的搜索性能。初步实验表明，新算法能有效地求解多目标优化问题。
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| 关 键 词： | 多目标优化 差分演化 种群多样性 Pareto最优 |
A Multi-Objective Differential Evolution Algorithm with Maintaining Diversity |
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| AO You-yen,LI Feng. A Multi-Objective Differential Evolution Algorithm with Maintaining Diversity[J]. Computer Engineering & Science, 2008, 30(12): 75-78 |
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| Authors: | AO You-yen LI Feng |
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| Affiliation: | AO You-yun1,LI Feng2 |
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| Abstract: | Differential evolution is a simple and effective evolutionary algorithm for global optimization.Through extending differential evolution to solve multi-objective optimization problems,a multi-objective differential evolution algorithm with maintaining diversity is presented in this paper.In order to maintain diversity to improve the search performance,the algorithm employs an orthogonal design method to generate initial population,and modifies differential evolution operators.The primary experimental results show that the algorithm is effective for solving multi-objective optimization problems. |
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| Keywords: | multi-objective optimization differential evolution population diversity Pareto optimal |
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