论文部分内容阅读
针对多寿命件机会更换问题缺乏快速有效求解算法的难题,提出了一种启发式搜索算法。以全生命周期寿命件总成本最低为优化目标,建立了多寿命件机会更换问题优化模型,将问题解空间表达为树结构;为了提高搜索算法的效率,提出了子节点生成方法和单层节点数量控制方法;在此基础上,提出了启发式搜索算法;最后,采用数值实验和应用案例对提出算法进行了评估和验证。结果表明:算法的消耗时间、求解效果与子节点生成系数α、单层节点最大数量β存在关系;当选取合适的α和β时,算法能够在较短时间内取得较好的效果;算法能够适用于设备总寿命为200000时间单位、包含100个寿命件的较大规模的多寿命件机会更换问题。
Aiming at the lack of a fast and effective solution to the chance replacement problem of multi-life components, a heuristic search algorithm is proposed. In order to optimize the goal of minimizing the total cost of life-cycle components in life cycle, an optimization model of chance-replacement problem for multi-life components is established, and the problem-solving space is expressed as a tree structure. In order to improve the efficiency of the search algorithm, Based on which, a heuristic search algorithm is proposed. Finally, numerical experiments and application cases are used to evaluate and verify the proposed algorithm. The results show that the algorithm consumes time, the solution effect and the sub-node generation coefficient α, the maximum number of single-layer nodes β relationship; when the appropriate choice of α and β, the algorithm can achieve better results in a relatively short period of time; Suitable for large-scale multi-life parts with a total equipment life of 200,000 time units, including 100 life parts, to be replaced.