Distributed project scheduling with information sharing in supply chains: Part i - An agent-based negotiation model

J. S.K. Lau, G. Q. Huang, K. L. Mak, L. Liang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

41 Citations (Scopus)


Distributed project scheduling problem (DPSP) in supply chains is concerned with configuration and scheduling of multiple projects in a network of independent and autonomous enterprises. Individual enterprises must collaborate with each other during two main stages: the configuration of a project - selection of contractors for performing project operations and the project scheduling - determining when the operations start. However, the collaboration is especially difficult because none of these enterprises holds the global information about the entire supply chain and all constituent enterprises. Instead, they have to capitalize whatever information is shared between them in order to solve their own local problems in a distributed and autonomous fashion. It is essential for the solution process to strike an overall balance between effectiveness and efficiency. The research, reported in this two-part paper, is aimed at proposing a negotiation-based algorithm for solving DPSP. Its emphasis is how to improve the convergence and quality of the solution by taking advantage of inter-enterprise information sharing especially the sharing of schedule flexibility information (SFI). The first part of this paper describes a new agent-based approach to DPSPs in supply chains while the second part will present detailed discussion on the theoretical and experimental analysis.

Original languageEnglish
Pages (from-to)4813-4838
Number of pages26
JournalInternational Journal of Production Research
Issue number22
Publication statusPublished - 15 Nov 2005
Externally publishedYes


  • Agent-based modelling
  • Distributed scheduling
  • Information sharing
  • 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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