计算机与现代化 ›› 2011, Vol. 1 ›› Issue (1): 52-3.doi: 10.3969/j.issn.1006-2475.2011.01.015

• 算法分析与设计 • 上一篇    下一篇

基于人工鱼群算法的机车二系支承载荷调整优化方法

杨本磊,潘迪夫   

  1. 中南大学交通运输工程学院,湖南 长沙 410075
  • 收稿日期:2010-09-01 修回日期:1900-01-01 出版日期:2011-01-20 发布日期:2011-01-20

Optimization Model of Locomotive Secondary Spring Load Adjustment Based on Artificial Fishswarm Algorithm

YANG Benlei, PAN Difu   

  1. School of Traffic & Transportation Engineering, Centre South University, Changsha 410075, China
  • Received:2010-09-01 Revised:1900-01-01 Online:2011-01-20 Published:2011-01-20

摘要:

人工鱼群算法是一种新型寻优策略,该算法对初值和参数不敏感,具有克服局部极值,获得全局最优解的能力。本文针对电力机车二系支承载荷调整数学模型,运用人工鱼群算法建立相应的优化模型,提出一种机车二系支承载荷调整的新方法。对国产HXD1B型机车试验结果表明:(1)该方法能一致收敛到全局最优解,算法稳定、可靠;(2)在相同初始群体条件下,与遗传算法相比,人工鱼群算法显著提高收敛速度,减少计算量和计算时间。

关键词: 人工鱼群算法, 机车二系载荷, 优化方法

Abstract:

As a new optimization strategy, Artificial Fishswarm Algorithm(AFSA)is not sensitive to initial parameters and values, has the abilities to overcome the local minimum and obtain the global optimum solution. According to the mathematical model of the electric locomotive’s secondary spring loads adjustment, a corresponding optimal model based on AFSA is presented and a method to the electric locomotive’s secondary spring loads adjustment is proposed for the first time. Results of simulation on HXD1B locomotive show that: (1) The method can converge to the same global optimal solution, and the algorithm is stable and reliable; (2) Comparing with the genetic algorithm, AFSA obviously improves the convergence speed and reduces calculated amount and computing time under the condition of the same initial group.

Key words: Artificial Fishswarm Algorithm, locomotive’s secondary spring loads, optimal method