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非线性约束优化问题的混合粒子群算法

高岳林1, 李会荣2   

  1. 1. 北方民族大学信息与系统科学研究所, 银川 750021;
    2. 商洛学院数学与计算科学系, 陕西商洛 726000
  • 收稿日期:2008-12-09 出版日期:2010-05-15 发布日期:2010-06-30
  • 基金资助:

    国家自然科学基金项目资助(60962006); 宁夏自然科学基金项目资助(NZ0848)

高岳林, 李会荣. 非线性约束优化问题的混合粒子群算法[J]. 计算数学, 2010, 32(2): 135-146.

Gao Yuelin, Li Huirong. HYBRID PARTICLE SWARM ALGORITHM OF NONLINEAR CONSTRAINT OPTIMIZATION PROBLEMS[J]. Mathematica Numerica Sinica, 2010, 32(2): 135-146.

HYBRID PARTICLE SWARM ALGORITHM OF NONLINEAR CONSTRAINT OPTIMIZATION PROBLEMS

Gao Yuelin1, Li Huirong2   

  1. 1. Research Institute of Information and System Science, North National University, Yinchuan 750021, China;
    2. Department of Mathematics and Computation Science, Shangluo University, Shangluo 726000, Shanxi, China
  • Received:2008-12-09 Online:2010-05-15 Published:2010-06-30
把处理约束条件的一个外点方法和改进的粒子群优化算法相结合, 提出了一种求解非线性约束优化问题的混合粒子群优化算法. 该方法兼顾了粒子群优化和外点法的优点, 对算法迭代过程中出现不可行粒子, 利用外点法处理后产生可行粒子. 数值实验表明了提出的新算法具有有效性、通用性和稳健性.

 

Combining an outside point method of dealing with the constraints with improved particle swarm optimization algorithm, a hybrid particle swarm optimization algorithm is proposed for solving non-linear constrained optimization problems. This method makes use of advantages of the PSO and outside point method. The non-feasible particles produced in iterative process are dealt with by the outside point method to produce feasible particles. A number of numerical experiments show that the proposed new algorithm has effectiveness and versatility and robustness.

 

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