Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

A. K. Tripathi, M. K. Tiwari, Tung Sun Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)


Agent technology is currently being considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. A multi-agent-based approach for solving the part allocation problems in flexible manufacturing systems (FMS) is presented that can easily cope with the dynamic environment. Four agents were involved in carrying out the tasks of allocating parts on different machines: communicator, machine, part and material handling device (MHD). Upon arrival in the manufacturing facility, the part informs the communicator agent about the task requirements. The communicator agent divides the task into subtasks and sends a call-for-bids message to the machine and MHD agents. Each machine responds in accordance with its process capabilities and buffer limit. This response may be for the whole task or for one or more subtasks and it contains the price and cost details for these subtasks along with the performance index and acceptance ratio of the machine. The final allocation is made based on the objective function that includes processing and transportation costs and time. An algorithm is presented that is used by the communicator agent for allocating parts to different machines. An illustrative example is given to solve the task allocation on five machines, with each machine having different performance index and acceptance ratio.
Original languageEnglish
Pages (from-to)1313-1335
Number of pages23
JournalInternational Journal of Production Research
Issue number7
Publication statusPublished - 1 Apr 2005
Externally publishedYes


  • Flexible Manufacturing Systems (FMS)
  • Multi Agent Systems (MAS)
  • Part selection
  • Task allocation

ASJC Scopus subject areas

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


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