| 一个求解约束优化问题的与可行基规则相结合的改进微粒群算法 |
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| 引用本文： | 刘国志,杜翼辰.一个求解约束优化问题的与可行基规则相结合的改进微粒群算法[J].长春理工大学学报,2010,33(1):156-158. |
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| 作者姓名： | 刘国志 杜翼辰 |
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| 作者单位： | 辽宁石油化工大学理学院信息与计算科学系,抚顺,113001;中山大学数学与计算科学学院,中山,510006 |
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| 基金项目： | 国家自然科学基金(50771052) |
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| 摘 要： | 提出一个求解约束最优化问题的新的混合算法-与可行基规则相结合的改进的微粒群算法。与惩罚函数法相比,可行基规则不需要额外的参数,且指引粒子迅速飞向可行域。利用5个基准测试函数进行仿真计算比较,仿真结果表明了新算法是求解约束最优化问题的一个高效的算法。
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| 关 键 词： | 可行基规则 微粒群算法 约束最优化 |
A Hybrid Improved Particle Swarm Optimization with a Feasibility-based Rule for Constrained Optimization |
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| LIU Guozhi,DU Yichen.A Hybrid Improved Particle Swarm Optimization with a Feasibility-based Rule for Constrained Optimization[J].Journal of Changchun University of Science and Technology,2010,33(1):156-158. |
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| Authors: | LIU Guozhi DU Yichen |
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| Affiliation: | 1.College of Science;Liaoning University of Petroleum & Chemical Technology;Fushun 113001;2.Department of mathmatics & Applied mathmatics;Sun Yat-sen University School of Mathmatics & Computational Science;Zhongshan 510006 |
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| Abstract: | In this paper the hybrid improved particle swarm optimization(HIPSO) with a feasibility-based rule is proposed to solve constrained optimization problems. In contrast to the penalty function method,the rule requires no additional parameters and can guide the swarm to the feasible region quickly. Simulation and comparisons based on several well-studied benchmarks demonstrate the effectiveness,efficiency and robustness of the proposed HIPSO. |
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| Keywords: | feasibility-based rule Particle swarm optimization unconstrained optimization |
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