计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 178-180.

• CRSSC-CWI-CGrC2015 • 上一篇    下一篇

求解非线性约束问题的混合粒子群优化算法

张利凤,胡小兵   

  1. (重庆大学数学与统计学院 重庆401331)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Hybrid Particle Swarm Algorithm of Solving Nonlinear Constraint Optimization Problems

ZHANG Li-feng,HU Xiao-bing   

  • Online:2018-11-16 Published:2018-11-16

摘要: 将处理约束问题的乘子法与改进的粒子群算法相结合,提出了一种求解非线性约束问题的混合粒子群算法。此算法兼顾了粒子群优化算法和乘子法的优点,对迭代过程中出现的不可行粒子,利用乘子法处理后产生可行粒子,然后用改进的粒子群算法来搜索其最优解,这样不仅减小了粒子群算法在寻优过程中陷入局部极小的概率,而且提高了搜索精度。数值试验结果表明提出的新算法具有搜索精度更高、稳定性更强、鲁棒性更好等特点。

关键词: 非线性约束优化,粒子群算法,乘子法

Abstract: Combining a multiplier method which deals with constraint problems with improved particle swarm optimization algorithm, a new hybrid particle swarm optimization algorithm was proposed for solving non-linear constraint problems. The new algorithm takes advantage of the particle swarm optimization algorithm and the multiplier method, for the non-available particle appearing in the iterative process, using the multiplier method to produce feasible particle, and then search its optimal value by improved particle swarm optimization. Thus it can not only reduce the probability of falling into local minimum, but also can improve the search accuracy. And the numerical tests show that the proposed new algorithm has the characteristics of validity and searching for more precise particle and better robustness.

Key words: Non-linear constraint optimization, Particle swarm optimization algorithm, Multiplier method

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