Real-time scheduling of batch processes via agent-based modeling

Yunfei Chu, John M. Wassick, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

We propose a novel agent-based method for real-time scheduling of network batch processes. The agent architecture is formulated based on the resource-task network (RTN) or state-task network (STN) representation so it is applicable to a wide range of network batch scheduling problems. A scheduling algorithm is developed based on the predicted objective function value by simulating another agent-based system. An embedded agent-based system is resulted in. The agent-based modeling provides an efficient heuristic method for solving a complicated batch scheduling problem. The case study demonstrates that the agent-based method is able to return a solution very close to the optimal one. However, the agent-based method significantly reduces the computational complexity. The efficiency enables the online real-time rescheduling under uncertainties.

Original languageEnglish (US)
Article number6426714
Pages (from-to)6370-6375
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
StatePublished - Dec 1 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: Dec 10 2012Dec 13 2012

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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