Efficient scheduling method of complex batch processes with general network structure via agent-based modeling

Yunfei Chu, John M. Wassick, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

A novel efficient agent-based method for scheduling network batch processes in the process industry is proposed. The agent-based model is based on the resource-task network. To overcome the drawback of localized solutions found in conventional agent-based methods, a new scheduling algorithm is proposed. The algorithm predicts the objective function value by simulating another cloned agent-based model. Global information is obtained, and the solution quality is improved. The solution quality of this approach is validated by detailed comparisons with the mixed-integer programming (MIP) methods. A solution close to the optimal one can be found by the agent-based method with a much shorter computational time than the MIP methods. As a scheduling problem becomes increasingly complicated with increased scale, more specifications, and uncertainties, the advantages of the agent-based method become more evident. The proposed method is applied to simulated industrial problems where the MIP methods require excessive computational resources.

Original languageEnglish (US)
Pages (from-to)2884-2906
Number of pages23
JournalAICHE Journal
Volume59
Issue number8
DOIs
StatePublished - Aug 1 2013

Keywords

  • Agent-based modeling
  • Batch processes
  • Efficient scheduling
  • General network structure
  • Mixed-integer programming

ASJC Scopus subject areas

  • Biotechnology
  • Environmental Engineering
  • Chemical Engineering(all)

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