摘要
维修保障资源优化集成作为保障资源分析的一个关键问题,是一个典型的集合覆盖问题,属于经典的N-P难题;针对现有优化方法存在的不足,通过对保障资源优化集成问题的分析,提出一种基于混沌遗传算法的保障资源优化方法;算法以遗传算法为主流程,利用混沌现象不重复遍历的特点优化生成初始种群,然后对每次迭代中的个体以一定的概率进行混沌优化;以C17电路为例,对算法的有效性进行了验证,结果表明,与传统方法相比较,该方法搜索速度快,优化效果明显,该方法已在工程实践得到应用。
Maintenance Support Resources Optimization is a key problem of support resources analysis, and it is also a traditional set covering problem, which belongs to an N--P completeness problem. It puts forward a Maintenance Support Resources optimization method based on Chaos Genetic Algorithm to overcome the shortages of existing methods. This improved algorithm takes GA as the main flow, and uses the character of traversing without repeat of chaos to optimize the initial group and then optimizes each individual with certain probabili- ty. It takes C17 circuit as an example to validate effectiveness of this improved algorithm. It shows that this algorithm searching speed is faster than traditional methods, and the optimal results are also better. The method has been used in engineering practice.
出处
《计算机测量与控制》
CSCD
北大核心
2012年第3期741-743,746,共4页
Computer Measurement &Control
关键词
保障资源优化
集合覆盖
混沌遗传算法
maintenance support resources optimization
set covering
Chaos genetic algorithm
