TY - JOUR
T1 - Exact algorithms for the feedback length minimisation problem
AU - Shang, Zhen
AU - Zhao, Songzheng
AU - Qian, Yanjun
AU - Lin, Jun
N1 - Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/1/17
Y1 - 2019/1/17
N2 - Planning the sequence of interrelated activities of production and manufacturing systems has become a challenging issue due to the existence of cyclic information flows. This study develops efficient exact algorithms for finding an activity sequence with minimum total feedback length in a design structure matrix. First, we present two new properties of the problem. Second, based on the properties, we develop an efficient Parallel Branch-and-Prune algorithm (PBP). Finally, the proposed PBP is further improved by adopting hash functions representing activity sequences, which is referred as hash function-based PBP. Experimental results indicate that the proposed hash function-based PBP can find optimal solutions for problems up to 25 interrelated activities within 1 h, and outperforms existing methods.
AB - Planning the sequence of interrelated activities of production and manufacturing systems has become a challenging issue due to the existence of cyclic information flows. This study develops efficient exact algorithms for finding an activity sequence with minimum total feedback length in a design structure matrix. First, we present two new properties of the problem. Second, based on the properties, we develop an efficient Parallel Branch-and-Prune algorithm (PBP). Finally, the proposed PBP is further improved by adopting hash functions representing activity sequences, which is referred as hash function-based PBP. Experimental results indicate that the proposed hash function-based PBP can find optimal solutions for problems up to 25 interrelated activities within 1 h, and outperforms existing methods.
KW - Branch-and-Prune Algorithm
KW - design structure matrix
KW - hash function
KW - iterative process
KW - production and manufacturing system
UR - https://www.scopus.com/pages/publications/85046032098
U2 - 10.1080/00207543.2018.1456697
DO - 10.1080/00207543.2018.1456697
M3 - 文章
AN - SCOPUS:85046032098
SN - 0020-7543
VL - 57
SP - 544
EP - 559
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 2
ER -