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 language | English (US) |
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Article number | 6426714 |
Pages (from-to) | 6370-6375 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
DOIs | |
State | Published - 2012 |
Event | 51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States Duration: Dec 10 2012 → Dec 13 2012 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization