基于模拟退火离散粒子群算法的测试点优化

doi:10.11772/j.issn.1001-9081.2014.06.1649

计算机应用 ›› 2014, Vol. 34 ›› Issue (6): 1649-1652.DOI: 10.11772/j.issn.1001-9081.2014.06.1649

基于模拟退火离散粒子群算法的测试点优化

焦晓璇¹,景博¹,黄以锋¹,邓森¹,窦雯²

1. 空军工程大学航空航天工程学院,西安 710038
2. 空军驻成都地区军事代表局,成都 610000

收稿日期:2013-11-27 修回日期:2014-01-03 出版日期:2014-06-01 发布日期:2014-07-02
通讯作者: 焦晓璇
作者简介:焦晓璇(1990-),男,山西运城人,硕士研究生,主要研究方向:故障诊断、测试性优化设计和验证评估;景博(1965-),女,河北邯郸人,教授,博士生导师,博士,主要研究方向:故障预测与健康管理、可测试性设计、传感器网络、数据融合;黄以锋(1984-),男,湖南耒阳人,讲师,博士,主要研究方向:测试性优化设计与验证评估、故障诊断与预测。
基金资助:
国家自然科学基金资助项目;航空科学基金资助项目

Optimization for test selection based on simulated annealing binary particle swarm optimization algorithm

JIAO Xiaoxuan¹,JING Bo¹,HUANG Yifeng¹,DENG Sen¹,DOU Wen²

1. College of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an Shaanxi 710038,China;
2. Air Force Representative in Chengdu Military Administration, Chengdu Sichuan 610000, China

Received:2013-11-27 Revised:2014-01-03 Online:2014-06-01 Published:2014-07-02
Contact: JIAO Xiaoxuan

摘要/Abstract

摘要：

针对复杂系统的测试点优化问题,提出一种基于模拟退火离散粒子群（SA-BPSO）算法的测试点优化算法。该算法利用模拟退火算法的概率突跳能力,克服了基本粒子群算法易陷入局部最优解的缺陷。阐述了该算法在系统测试点优化应用中的流程及关键步骤,并且理论分析了该算法的复杂度。仿真结果表明,该算法在计算时间和测试费用方面都优于遗传算法,能够应用于复杂系统的测试点优化。

Abstract:

For the problem of test selection for complex system, a test selection optimization based on Simulated Annealing Binary Particle Swarm Optimization (SA-BPSO) algorithm was adopted. The probabilistic jumping ability of simulated annealing algorithm was used to overcome the deficiencies of the particle swarm being easily fall into local optimal solution. The process and key steps of the algorithm for test selection in complex system were introduced, and the complexity of the algorithm was analyzed. The simulation results show that the algorithm has better performance in running time and testing cost compared to genetic algorithm, thus the algorithm can be used to optimize test points of complex system.

中图分类号:

TP206

焦晓璇景博黄以锋邓森窦雯. 基于模拟退火离散粒子群算法的测试点优化[J]. 计算机应用, 2014, 34(6): 1649-1652.

JIAO Xiaoxuan JING Bo HUANG Yifeng DENG Sen DOU Wen. Optimization for test selection based on simulated annealing binary particle swarm optimization algorithm[J]. Journal of Computer Applications, 2014, 34(6): 1649-1652.

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基于模拟退火离散粒子群算法的测试点优化

Optimization for test selection based on simulated annealing binary particle swarm optimization algorithm

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