摘要
测试流程的优化是测试性方案优化工作的开始,关系到整个测试性设计的好坏。针对现有优化方法的不足,提出带自适应变异的质心量子粒子群算法(AMCQPSO),为粒子群增加质心粒子、建立收缩扩张系数的自适应调节机制,并且引入变异因子,提高算法收敛速度的同时,增强了全局搜索能力,有效地避免了"早熟"现象。最后通过实例验证了算法的有效性,能够实现测试流程的优化。
Optimization of testing procedure is which has close relation with testability design. methods, a means of AMCQPSO was given in the first step for optimizing testabihty prbject, In order to overcome the disadvantages of current this paper. This method designs the eentroid of particle swarm, builds up the adaptive model for shrink and expand coefficient and introduces mutation. These ameliorations effectively meet the expected requirements, not only speed up the convergence, but also gain the ability of all-around searching. This method was evaluated by some experiments and it is able to realize the optimization of testing procedure.
出处
《中国测试》
CAS
北大核心
2012年第5期84-87,共4页
China Measurement & Test
关键词
测试流程优化
自适应变异
质心量子粒子群
测试性设计
testing procedure optimization
adaptive mutation
centroid quantum particle swarm optimization
testability design
