A double-decomposition based parallel exact algorithm for the feedback length minimization problem

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 ma...

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Vydané v:PeerJ. Computer science Ročník 9; s. e1597
Hlavní autori: Shang, Zhen, Hao, Jin-Kao, Ma, Fei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: San Diego, USA PeerJ. Ltd 15.09.2023
PeerJ Inc
Predmet:
Algorithms
Algorithms and Analysis of Algorithms
Branch-and-prune algorithm
Cost control
Design structure matrix
Distributed and Parallel Computing
Optimization Theory and Computation
Parallel exact algorithm
Product development
ISSN:2376-5992, 2376-5992
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Shrnutí: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 h, and outperforms state of the art exact algorithms.
Bibliografia:ObjectType-Article-1
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content type line 23
ISSN:2376-5992
2376-5992
DOI:10.7717/peerj-cs.1597