Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, scheduling interrelated activities in an appropriate sequence is an important issue for project managers. This study develops a double-decomposition based parallel branch-and-prune algorithm, to determine the optimal activity sequence that minimizes the total feedback length (FLMP). This algorithm decomposes FLMP from two perspectives, which enables the use of all available computing resources to solve subproblems concurrently. In addition, we propose a result-compression strategy and a hash-address strategy to enhance this algorithm. Experimental results indicate that our algorithm can find the optimal sequence for FLMP up to 27 activities within 1 hour, and outperforms state of the art exact algorithms.

翻译：产品开发项目通常包含许多相互关联的活动，这些活动之间具有复杂的信息依赖关系，可能导致活动返工、项目延迟和成本超支。为减少负面影响，按适当顺序安排相互关联的活动是项目管理人员面临的重要问题。本研究提出了一种基于双重分解的并行分支剪枝算法，用于确定最小化总反馈长度（FLMP）的最优活动序列。该算法从两个角度对FLMP进行分解，从而能够利用所有可用计算资源并行求解子问题。此外，我们提出了结果压缩策略和哈希地址策略来增强该算法。实验结果表明，我们的算法能在1小时内求解最多包含27个活动的FLMP最优序列，且优于现有最先进的精确算法。