| 基于蚁群算法的MAS多目标协调优化 |
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| 引用本文： | 郭红霞,吴捷,黄飞龙.基于蚁群算法的MAS多目标协调优化[J].控制与决策,2007,22(8):946-950. |
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| 作者姓名： | 郭红霞 吴捷 黄飞龙 |
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| 作者单位： | 华南理工大学,电力学院,广州,510640 |
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| 基金项目： | 国家自然科学基金重点项目（60534040）. |
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| 摘 要： | 利用蚁群算法的群体搜索策略,研究了基于蚁群算法的MAS多目标协调优化机制．对每个Agent的目标函数分配一群蚂蚁。使之在问题空间寻优,并对所有的优化解采用谈判机制进行协调,以产生多目标优化问题的Pareto折衷解．采用“误差率”和“空间矩阵”方法对算法的性能指标进行度量．用该方法求解两个典型的多目标优化测试函数,仿真结果表明所提出的方法可成功地解决MAS的多个目标函数的优化问题,收敛速度较快．
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| 关 键 词： | 蚁群算法 多目标协调优化 谈判机制 |
| 文章编号： | 1001-0920（2007）08-0946-05 |
| 收稿时间： | 2006/3/21 0:00:00 |
| 修稿时间： | 2006-03-212006-07-07 |
Multi-objective coordinated optimal of MAS based on ant system |
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| GUO Hong-xia,WU Jie,HUANG Fei-long.Multi-objective coordinated optimal of MAS based on ant system[J].Control and Decision,2007,22(8):946-950. |
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| Authors: | GUO Hong-xia WU Jie HUANG Fei-long |
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| Affiliation: | College of Electrical Power, South China University of Technology, Guangzhou 510640, China |
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| Abstract: | A mechanism of multiple objective coordinated optimization based on ant system for MAS is proposed by using colony searching strategy.A family of ants is assigned for each objective of each agent,by which the optimal solution is searched in solution space.Negotiation mechanism is applied to coordinate all the solutions.Performance is measured by usihg "error ratio" and "spacing" metrics.Multiple objective coordinated optimization based on ant system is applied to two typical multiple objective test functions.Simulation results show that this algorithm is able to solve the multiple objective optimization problems successfully and has fast convergence speed. |
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| Keywords: | Ant system Multiple-objective coordinated optimization Negotiation mechanism |
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