Collective intelligence on dynamic manufacturing scheduling optimization

Swarm Intelligence (SI) is a growing research field of Artificial Intelligence (AI). SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviours of insects and of other animals. This paper presents hybridization and combination of different AI approaches, like Bio-Inspired Techniques (BIT), Multi-Agent systems (MAS) and Machine Learning Techniques (ML T). The resulting system is applied to the problem of jobs scheduling to machines on dynamic manufacturing environments.

[1]  Russell C. Eberhart,et al.  Tracking and optimizing dynamic systems with particle swarms , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[2]  Qing He,et al.  Multi-Agent Cooperation Based on Interest Group , 2009, 2009 International Conference on Computational Intelligence and Software Engineering.

[3]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[4]  Qing-song Li,et al.  Model Design of Job Shop Scheduling Based on Multi-agent System , 2009, 2009 IITA International Conference on Services Science, Management and Engineering.

[5]  C. Ramos,et al.  Cooperation Mechanism for Team-Work based Multi-Agent System in Dynamic Scheduling through Meta-Heuristics , 2007, 2007 IEEE International Symposium on Assembly and Manufacturing.

[6]  Sanja Petrovic,et al.  Inter-agent cooperation and communication for agent-based robust dynamic scheduling in steel production , 2004, Advanced Engineering Informatics.

[7]  Egon Balas,et al.  The Shifting Bottleneck Procedure for Job Shop Scheduling , 1988 .

[8]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[9]  Xia Hong,et al.  Multi-Agent Based Scheduling for Batch Process , 2007, 2007 8th International Conference on Electronic Measurement and Instruments.

[10]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[11]  Thomas Stützle,et al.  Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .