深度优先搜索在耦合任务集识别中的应用

在复杂产品项目管理中,合理的任务分解可以优化资源配置和利用,降低设计过程中任务间的信息交互复杂度和约束度.耦合任务集是任务分解后得到的一组具有相互依赖关系的任务集合,它反映了设计过程对多领域知识集成的要求,对设计时间和资源配置均有着关键影响.通过对设计过程所转化的有向图以及其转置图,使用深度优先搜索算法,旨在找出有向图中的强连通分支,以实现对设计过程中耦合任务集的识别.给出了识别设计过程中的耦合任务集的算法步骤,并利用实例对算法如何识别耦合任务集进行了说明,证明了该方法对设计过程中耦合任务集的识别是准确有效的.

The application of Depth first search in identifying coupled task sets

In the project management for complex product, reasonable decomposition of task can optimize deploying of the resource and cut down the interaction complexity and restriction among tasks in product design process. The coupled task sets are a type of tasks set which have mutual dependency relationship after task decomposition. They reflect the design process demanding for multi-domain knowledge integration and have a crucial effect on the time of design and deploying of the resource. By using arithmetic of depth first search in directed graph transformed from design process and transposed graph, this paper finds out the strongly connected component and distinguishes the coupled task sets. The calculation steps of identifying the coupled task sets are given. Finally a example of the algorithm principle is explained, proved that the method of identifying coupled task sets in the design process is correct and effective.