摘要系统部件适当的冗余，可以保证系统在最优经济效益下，获得更高的可靠性。 然而在如何获取最优可靠度解值上，过往的经验法处理线性系统优化时较为简便， 但对复杂系统往往难以得到最优解，由此兴起的启发式算法，取得了突破性进展。 但是此类非线性问题，计算量庞大，常规数学运算不太适用，因此需要实现智能优 化设计。84396

本文首先介绍了可靠性冗余的起源及发展历程，国内外的现状及应用等。其次 着重介绍了启发式算法中的遗传算法，并将其与其它算法进行比较，用以表明本设 计最终选用遗传算法的科学性与实用性。再次，详细介绍了优化设计的整体流程以 及为提升解值适应度所做的一些尝试。本设计中，选用二进制编码，基于轮盘赌的 染色体选择方式，单点的前部交叉操作以及基因值加随机数的变异操作。在适应度 函数构建上，尝试了成本与可靠度的同步求解。综合采用以上方法以求避免不可行 解的出现，并得出优化最优解。

最后，选择两个具有代表性的案例，对设计方案进行实际验证。实验结果显示， 本设计可以在符合系统要求的前提下，获得相对其它方案效益比更高的解。

毕业论文关键词：系统可靠性；遗传算法；可靠性优化

ABSTRACT Appropriate redundancy of system components can ensure the system under optimal economic efficiency getting greater reliability。 However,in how to obtain the optimal reliability solution value and method of past experience handling linear system optimization is the simple, but for complex systems is often difficult to get the optimal solution, thus the rise of heuristic algorithm and achieved a breakthrough。 But this kind of non-linear problem, the computation quantity is huge, the conventional mathematics operation is not suitable, therefore needs to realize the intelligent optimization design。

In the first part of this paper, introducing the origin and development of reliability redundancy, the present situation and application of the domestic and foreign。 Secondly, this paper introduces the genetic algorithm in the heuristic algorithm, and compares it with other algorithms to show that the genetic algorithm is scientific and practical。Thirdly, it introduces the overall design and process optimization to enhance the value of the attempt to adapt to some degree In this design, binary coding is used, based on the chromosome selection method, single point of the front intersection operation and gene value plus random number of variation operation。 In the fitness function construction, the cost and reliability of the synchronous solution。 In order to avoid the emergence of infeasible solutions, the above method is adopted to obtain the optimal solution。

Finally, choose two representative cases, the design of the actual verification。 The experimental results show that the design can obtain the solution with higher efficiency than other schemes under the premise of the system requirements。

Keywords:System Reliability;Genetic Algorithm; Reliability Optimization

第一章 绪论 1 1。1 可靠性相关介绍 1

1。1。1 国外的可靠性起源及发展历程 1

1。1。2 我国的可靠性起源及发展历程 2

1。1。3 国内外可靠性发展现状 2

1。1。4 可靠性的应用 3

1。2 研究的意义及内容 4

1。2。1 本设计的研究意义 4

1。2。2 本设计的主要研究内容