摘要
系统可靠性优化已被证明是一个NP完全问题,不存在精确的求解方法。人们构造了大量的启发式算法,如遗传算法(GA),蚁群算法(ACO),模拟退火算法(SA)等。针对各种算法所存在的早熟收敛,易陷入局部极值点的缺点,提出了将粒子群算法(particle swarm optimization,PSO)用于求解可靠性问题。给出了基于粒子群算法的可靠性优化求解策略,根据数学模型,详细讨论了求解步骤,最后给出了实验仿真结果。结果表明该算法具有较强的局部搜索能力,同时也有更高的搜索效率,与其它方法相比,该算法能够找到更优解,验证了该算法的可行性和有效性。
Optimization of system reliability is a NP hard problem, and people can not find the precise method for result. Many have put forward many heuristic algorithms, such as Genetic algorithm, Simulated Annealing algorithm, Ant Colony Optimization, etc. But these algorithms had some flaws at the moment, such as early convergence and easily falling in local peak, etc. The paper put forward Particle Swarm Optimization Algorithm for Optimization of system reliability. To the problem of optimization of system relia- bility, it discussed the solving strategy based on PSO. According to the mathematic model, the detailed steps put forward. At last, by calculations of the example and comparison with other algorithms, it proves the algorithm has much stronger ability of local search and better search efficiency. It also can find better solution. It certifies that this method is feasible and valid.
出处
《台州学院学报》
2006年第6期29-32,共4页
Journal of Taizhou University
关键词
粒子群算法
可靠性
优化
集群智能
particle group algorithm
reliability
optimization
swarm intelligence
