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A Particle Swarm Algorithm for Optimization of Complex System Reliability

机译:优化复杂系统可靠性的粒子群算法

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摘要

In recent years, a broad class of stochastic metaheuristics, such as Tabu search, simulated annealing, genetic algorithm, particle swarm optimization, ant colony optimization etc. has been applied for reliability optimization problems. In this paper a particle swarm optimization algorithm is presented. Then, the performance of the proposed algorithm is tested on some complex engineering optimization problems. They are three well-known complex reliability optimization problems. Finally, the results are compared with those given by several well-known methods. Numerical experiments demonstrate that the proposed method is promising and the results obtained by proposed algorithm are either superior or comparable to the previously best known results presented in literature for reliability optimization of complex systems in terms of computation time as well as solution quality.
机译:近年来,诸如Tabu搜索,模拟退火,遗传算法,粒子群优化,蚁群优化等广泛的随机元启发式算法已被用于可靠性优化问题。本文提出了一种粒子群优化算法。然后,在一些复杂的工程优化问题上测试了该算法的性能。它们是三个众所周知的复杂可靠性优化问题。最后,将结果与几种众所周知的方法给出的结果进行比较。数值实验表明,所提出的方法是有前途的,并且所提出的算法所获得的结果在计算时间和解决方案质量方面优于或优于文献中针对复杂系统的可靠性优化所提供的文献。

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