Computer and Modernization ›› 2011, Vol. 1 ›› Issue (1): 52-3.doi: 10.3969/j.issn.1006-2475.2011.01.015

• 算法分析与设计 • Previous Articles     Next Articles

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

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