Abstract
Modern manufacturing systems have to cope with dynamic changes and uncertainties such as machine break down, hot orders and other kinds of disturbances. Holonic manufacturing systems (HMS) provide a flexible and decentralized manufacturing environment to accommodate changes dynamically. In this paper, A new class of Time Petri Nets(TPN), Buffer-nets, for defining a Scheduling Holon is proposed, which enhances the modeling techniques for manufacturing systems with features that are considered difficult to model. The proposed novel GA algorithm performs the population alternation according to the features of the evolution of the populations in natural. Simulation results show that the proposed GA is more efficient than standard GAs. The proposed HPGA synthesizes the merits in both PSO and GA. The simulation results of the example show that the methods to scheduling holon are effective for fulfilling the scheduling problem.
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Zhao, F., Yang, Y., Zhang, Q., Yi, H. (2006). Timed Petri-Net(TPN) Based Scheduling Holon and Its Solution with a Hybrid PSO-GA Based Evolutionary Algorithm(HPGA). In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_99
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DOI: https://doi.org/10.1007/978-3-540-36668-3_99
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