Improved Second-Order Oscillatory Particle Swarm Optimization

doi:10.3778/j.issn.1002-8331.1803-0364

Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (9): 130-138.DOI: 10.3778/j.issn.1002-8331.1803-0364

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Improved Second-Order Oscillatory Particle Swarm Optimization

JIANG Li1，2, YE Runzhou1，2, LIANG Changyong1，2, LU Wenxing1，2

1.School of Management, Hefei University of Technology, Hefei 230009, China
2.Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009, China

Online:2019-05-01 Published:2019-04-28

改进的二阶振荡粒子群算法

蒋丽1，2，叶润舟1，2，梁昌勇1，2，陆文星1，2

1.合肥工业大学管理学院，合肥 230009
2.过程优化与智能决策教育部重点实验室，合肥 230009

Abstract

Abstract: Aiming at some demerits of Particle Swarm Optimization（PSO）, such as falling into local optimum, analyzing the evolutionary equation of particle swarm optimization, an improved particle swarm optimization algorithm is proposed. The algorithm uses different parameters in the oscillation, which is used to adjust the global and local search capabilities of the particle swarm algorithm. The experimental results of the test function and the robot path planning are compared and analyzed with the experimental results of standard PSO, two-order PSO and two-order oscillating PSO algorithm, which verifies the effectiveness and feasibility of the improved algorithm.

Key words: Particle Swarm Optimization（PSO）, two-order oscillating evolutionary equation, convergence precision, robot path planning

摘要： 针对粒子群算法易陷入局部最优等问题，分析了粒子群算法的进化方程，提出了一种改进的粒子群优化算法。算法在振荡环节采用互不相同的参数取值来调节粒子群算法的全局和局部搜索能力，并通过对测试函数和机器人路径规划问题仿真模拟，与标准PSO、标准二阶PSO、二阶振荡PSO算法的实验结果进行对比分析，验证了所提出算法的有效性和可行性。

关键词: 粒子群算法, 二阶振荡进化方程, 收敛精度, 机器人路径规划

JIANG Li1，2, YE Runzhou1，2, LIANG Changyong1，2, LU Wenxing1，2. Improved Second-Order Oscillatory Particle Swarm Optimization[J]. Computer Engineering and Applications, 2019, 55(9): 130-138.

蒋丽1，2，叶润舟1，2，梁昌勇1，2，陆文星1，2. 改进的二阶振荡粒子群算法[J]. 计算机工程与应用, 2019, 55(9): 130-138.

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Improved Second-Order Oscillatory Particle Swarm Optimization

改进的二阶振荡粒子群算法

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