Article ID: | iaor20071753 |
Country: | United Kingdom |
Volume: | 44 |
Issue: | 22 |
Start Page Number: | 4793 |
End Page Number: | 4813 |
Publication Date: | Jan 2006 |
Journal: | International Journal of Production Research |
Authors: | Yu Xuefeng, Ram Bala |
Keywords: | agent technology |
Flexible routing requires scheduling to be responsive and robust. Multi-agent systems have the potential to achieve robustness and provide a means for real-time planning and scheduling. The objective of this paper is to propose a multi-agent scheduling system with a good solution quality and robustness. The proposed multi-agent approach is designed for dynamic job shops with routing flexibility and sequence-dependent setup. A bio-inspired strategy based on division of labour in insect societies is presented for coordination among agents. The strategy is accomplished using a computational model which is composed of response threshold, response intention, and machine-centred reinforcement learning. The bio-inspired scheduling is compared with an agent-based approach and a dispatching rule-based approach. The experiments were performed using simulation and statistical analysis. Results show that the proposed bio-inspired scheduling model performs better than the other two methods on all eight common scheduling metrics.