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.Comment: This paper has been accepted by PeerJ Computer Science on August 28,
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