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Volume 8 Issue 1
Jan.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Zhou He, Ziyue Ma, Zhiwu Li and Alessandro Giua, "Parametric Transformation of Timed Weighted Marked Graphs: Applications in Optimal Resource Allocation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 179-188, Jan. 2021. doi: 10.1109/JAS.2020.1003477
Citation: Zhou He, Ziyue Ma, Zhiwu Li and Alessandro Giua, "Parametric Transformation of Timed Weighted Marked Graphs: Applications in Optimal Resource Allocation," IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 179-188, Jan. 2021. doi: 10.1109/JAS.2020.1003477

Parametric Transformation of Timed Weighted Marked Graphs: Applications in Optimal Resource Allocation

doi: 10.1109/JAS.2020.1003477
Funds:  This work was supported by the National Natural Science Foundation of China (61803246, 61703321), the China Postdoctoral Science Foundation (2019M663608), Shaanxi Provincial Natural Science Foundation (2019JQ-022 and 2020JQ-733), the Fundamental Research Funds for the Central Universities (JB190407), and the Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology (SKL2020CP03)
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  • Timed weighted marked graphs are a subclass of timed Petri nets that have wide applications in the control and performance analysis of flexible manufacturing systems. Due to the existence of multiplicities (i.e., weights) on edges, the performance analysis and resource optimization of such graphs represent a challenging problem. In this paper, we develop an approach to transform a timed weighted marked graph whose initial marking is not given, into an equivalent parametric timed marked graph where the edges have unitary weights. In order to explore an optimal resource allocation policy for a system, an analytical method is developed for the resource optimization of timed weighted marked graphs by studying an equivalent net. Finally, we apply the proposed method to a flexible manufacturing system and compare the results with a previous heuristic approach. Simulation analysis shows that the developed approach is superior to the heuristic approach.

     

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  • 1 Although several techniques that may help to speed up the approaches in [30], [31] are developed, these procedures are still subject to high computational complexity.
    2 The solutions developed in [30] and [31] for the cycle time optimization have high computational cost since they require one to solve a mixed integer linear programming for each possible equivalent TMG system.
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    Highlights

    • A transformation method is developed for Timed Weighted Marked Graphs (TWMGs)
    • An analytical approach is proposed for the marking optimization problem of TWMGs
    • The proposed method is also applicable for solving cycle time optimization problem

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