结合模糊集理论与贪心算法的复杂产品设计任务动态规划方法研究

Research on dynamic programming method of complex product design task combining fuzzy set theory and greedy algorithm

  • 摘要: 在产品设计过程中,设计团队面临资源和时间分配不合理,任务执行存在先后顺序以及设计人员和任务受外部因素干扰导致项目延期的问题。首先,以历史设计案例中任务的执行时间作为参考时间,针对不同能力等级设计人员,结合模糊集理论对任务的执行时间进行量化;其次,通过构建多层级设计结构矩阵获取任务之间关系,并利用拓扑层级排序方式获取任务之间执行序列;最后,使用状态转移矩阵分析设计任务执行情况,并结合贪心算法,在满足任务时序和时长约束的条件下生成最优分配方案,该方案可在设计资源变更时动态调整并重新再分配。研究结果表明,以J企业某型号厢舱类产品为例,成功构建了设计任务执行时间矩阵及有向无环图,并通用贪心算法实现了任务的优化分配。

     

    Abstract: During the product design process, the design team faces issues such as unreasonable allocation of resources and time, the sequence of task execution, and project delays caused by external factors affecting designers and tasks. Firstly, historical design case execution times are used as reference times, and fuzzy set theory is applied to quantify the execution times of tasks by designers of different skill levels. Secondly, a multi-level design structure matrix is constructed to obtain the relationships between tasks, and a topological hierarchy sorting method is utilized to determine the execution sequence of tasks. Finally, a state transition matrix is employed to analyze the execution status of design tasks, and a greedy algorithm is combined to generate an optimal allocation scheme under the constraints of task sequence and duration, which can be dynamically adjusted and redistributed when design resources change. The research results indicate that, using a certain model of cabin-type products from Company J as an example, a design task execution time matrix and a directed acyclic graph have been successfully constructed, and the optimization of task allocation has been achieved through the greedy algorithm.

     

/

返回文章
返回