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Exact algorithms for the feedback length minimisation problem

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  • Zhen Shang
  • Songzheng Zhao
  • Yanjun Qian
  • Jun Lin

Abstract

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.

Suggested Citation

  • Zhen Shang & Songzheng Zhao & Yanjun Qian & Jun Lin, 2019. "Exact algorithms for the feedback length minimisation problem," International Journal of Production Research, Taylor & Francis Journals, vol. 57(2), pages 544-559, January.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:544-559
    DOI: 10.1080/00207543.2018.1456697
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