Multi-agent Formula for automated guided vehicles Systems

Authors

1 Golpayegan University of Technology, Department of Industrial Engineering, Golpayegan, Iran

2 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

Automated guided vehicle system (AGVS) is traditionally used in manufacturing and warehousing. Especially, AGVS has many applications in flexible manufacturing system (FMS) (see, e.g., Ganesharajah, Hall, & Sriskandarajah, 1998; Seo & Egbelu, 1999;
Vosniakos & Mamalis, (1990). Agents are event-driven objects that can integrant in automated manufacturing environments to control certain tasks. In this paper a set of agents (a multi-agent system) is introduced to control an automated manufacturing environment. The studied problem can be modeled as a job shop where the jobs have to transported between machines by AGVs. This article introduces based on a disjunctive graph to modulate the joint scheduling problem and for machines and AGVs scheduling. The objective is to minimize the make span. Some case studies were used to show the effectiveness of simulation in solving these problems

Keywords


Briskorn, D., Drexl, A. and Hartmann, S. (2006)– Inventory based Dispatching of Automated Guided Vehicles on Container Terminals, Institut für Betriebswirtschaftlehre, Lehrtuhl für Produktion & Logistik, Christian-Albrechts- Universität zu Kiel, Institut für Betriebswirtschaftlehre, Lehrtuhl für Produktion & Logistik, Christian-Albrechts- Universität zu Kiel, HPC Hamburg Port Consulting and HHLA Container Terminal Altenwerder Hamburg Germany, OR Spectrum.
Choobineh, F. and Suri, R. (1986), Flexible Manufacturing Systems, Current issues. Flores-Mendez, R.A. (1999). toward a standardization of multi-agent system frameworks, ACM Crossroads, Issue 5.4.
Ganesharajah, T., Hall, N.G. and Sriskandarajah, C. (1998). “Design and operational issues in AGVserved manufacturing systems”. Annals of Operations Research. Vol. 76, No. 0, pp. 109–154.
Grabowski, J., Nowicki, E., Zdrzalka, S., (1996). “A block approach for single machine scheduling with release dates and due dates”. European Journal of Operations Research. Vol. 26, No. 2, pp. 278– 285.
Li, D.C., Wu, C., Tong, K.Y. (1997). “Using an unsupervised neural network and decision tree as knowledge acquisition tools for FMS scheduling”, International Journal of System Science, Vol. 28, No.10, pp. 977-985.
Li, D.C., Chen, L.S. and Lin, Y.S. (2003). “Using functional virtual population as assistance to learn scheduling knowledge in dynamic manufacturing environments”, International Journal of Production Research, Vol. 41, No.17, pp. 4011-4024.
Rashidi, H. and Tsang, E.P.K. (2005). Applying the Extended Network Simplex Algorithm to Dynamic Automated Guided Vehicles Scheduling, Proceedings, 2nd Multidisciplinary Conference on Scheduling (MISTA), New York, USA, July.
Tempelmeir and Kuhn, H. (1986), Flexible Manufacturing System-Decision support for design and operation, Institute of Industrial Engineers
Yalcin, A. and Boucher, T.O. (2000). “Deadlock avoidance in flexible manufacturing systems using finite automata”, IEEE Transactions on Robotics and Automation, Vol. 16, No. 4, pp. 424-429.