Distributed project scheduling with information sharing in supply chains: Part II - Theoretical analysis and computational study

J. S.K. Lau, G. Q. Huang (Corresponding Author), K. L. Mak, L. Liang

Research output: Journal article publicationReview articleAcademic researchpeer-review

25 Citations (Scopus)

Abstract

The first part of this paper (Lau, J.S.K., Huang, G.Q. and Mak, K.L., Distributed project scheduling with information sharing in supply chains: part I - agent-based negotiation algorithm. Int. J. Prod. Res. , 2005, 43, 4813-4838) has outlined the background of this research. The paper proposes and demonstrates a new negotiation-based algorithm (NEG) for solving distributed project scheduling problems (DPSP). This new algorithm not only acknowledges and accommodates the autonomy and independence of individual enterprises in making decisions in the entire supply chain, but also takes advantage of limited information shared among them to improve the quality and efficiency. This second paper will conduct a thorough theoretical analysis and computational study on the proposed algorithm. The theoretical analysis shows that the algorithm converges such that schedules of project and contractor agents do not have conflicts. The computational study reveals that NEG performs better than a centralized heuristic and contract net protocols in terms of the solution quality (e.g. total operating cost). Computational efficiency of NEG is also reasonably comparable and competitive to the extent that good quality solutions can be obtained within an affordable time limit.

Original languageEnglish
Pages (from-to)4899-4927
Number of pages29
JournalInternational Journal of Production Research
Volume43
Issue number23
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes

Keywords

  • Agent-based modelling
  • Distributed scheduling
  • Negotiation-based scheduling
  • Supply chain project scheduling

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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