Bio-inspired scheduling for dynamic job shops with flexible routing and sequence-dependent setups
Authors: Yu, Xuefeng; Ram, Bala
Source: International Journal of Production Research, Volume 44, Number 22, 15 November 2006 , pp. 4793-4813(21)
Publisher: Taylor and Francis Ltd
Abstract: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.
Document Type: Research Article
Affiliations: Department of Industrial and Systems Engineering, North Carolina Agriculture and Technical State University, Greensboro, NC 27411, USA
Publication date: November 15, 2006