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一种改进的蚁群算法用于灰色约束非线性规划问题求解 被引量：2

Solution to Grey Constrained Nonlinear Programming Problem Based on Improved Ant Colony Algorithm
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摘要 针对灰色约束非线性规划问题,设计了一种改进蚁群算法.该算法采用了正反馈机制,在对灰色约束非线性规划问题白化处理后,将罚函数方法引入到目标函数中,同时给出了改进蚁群算法的仿真流程.实例应用表明,将改进后的蚁群算法应用于灰色约束非线性规划问题的求解是可行有效的. An improved ant colony algorithm was proposed to solve the grey constrained nonlinear programming problem. Positive feedback mechanism was adopted in this algorithm. On the basis of whitening the grey constrained nonlinear programming problem, penalty function method was introduced in the objective function. A detailed programming flow-chart was also presented. The practical simulation results show that the improved ant colony algorithm is feasible and effective in solving grey constrained nonlinear programming problem.
作者 段海滨 王道波 于秀芬 朱家强
机构地区 南京航空航天大学自动化学院 中国科学院空间科学与应用研究中心 清华大学智能技术与系统国家重点实验室
出处 《四川大学学报（自然科学版）》 CAS CSCD 北大核心 2004年第5期973-977,共5页 Journal of Sichuan University(Natural Science Edition)
基金 国家航空科学基金(01C52015) 江苏省"333"工程基金
关键词 灰色系统 灰色约束非线性规划问题 蚁群算法 信息素 grey system grey constrained nonlinear programming problem ant colony algorithm pheromone
分类号 O221.2 [理学—运筹学与控制论]
  • 相关文献

参考文献8

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二级参考文献26

  • 1MA Liang, WANG Long de College of Management, University of Shanghai for Science and Technology, Shanghai 200093, China.Artificial Ant Algorithm for Constrained Optimization[J].Journal of Systems Science and Systems Engineering,2001,13(1):57-61. 被引量：8
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共引文献64

同被引文献17

  • 1夏军,张祥伟.河流水质灰色非线性规划的理论与应用[J].水利学报,1993,25(12):1-9. 被引量：11
  • 2马良,朱刚,宁爱兵.蚁群优化算法[M].北京:科学出版社,2008,2.
  • 3邓聚龙.灰色多维规划[M].武汉:华中理工大学出版社,1988.
  • 4Liu S F, Jeffrey Y L F. Advances in Grey Systems Research[M]. Berlin: Springer, 2010.
  • 5Fang A G, Liu S F, Shi H X, et al. Grey Game Theory and Its Applications in Economic Decision- Making[M]. New York: Auerbach Publications, 2009.
  • 6Liu S F, Lin Y. Grey Systems: Theory and Applications[M]. Berlin: Springer, 2010.
  • 7Wen K L. Grey Systems: Modeling and Prediction[M].Tucson: Yang's Scientific Press, 2004.
  • 8Rashedi E, Nezamabadi-pour H, Saryazdi S. GSA: a gravitational search algorithm[J]. Information Science, 2009, 179(13): 2232-2248.
  • 9Rashedi E, Nezamabadi-pour H, Saryazdi S. BGSA: binary gravitational search algorithm[J]. Nat- ural Computing, 2010, 9(3): 727-745.
  • 10Rashedi E, Nezamabadi-pour H, Saryazdi S. Filter modeling using gravitational search algorithm[J]. Engineering applications of artificial Intelligence, 2011, 24: 117-122.

引证文献2

二级引证文献2

四川大学学报（自然科学版）
2004年 第5期

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