Real-Time Controlled Multi-objective Scheduling Through ANNs and Fuzzy Inference Systems: The Case of DRC Manufacturing.

In this paper, we developed an integrated multi-objective real-time controlled scheduling methodology for Dual Resource Constrained systems. The proposed methodology integrates simulation, neural network and fuzzy inference system approaches to obtain a schedule considering both state of the system and objectives. By means of a case study, we have demonstrated that the proposed methodology can be an effective tool for dynamic scheduling of DRC systems. [ABSTRACT FROM AUTHOR]