GRASP-based Approach for Minimum Initial Marking Estimation in Labeled Petri Nets

被引：1
|
作者：
Kmimech, Hichem [1 ]
Sliman, Layth [2 ]
Nabli, Lotfi [1 ]
机构：
[1] Univ Monastir, Res Lab Automat Signal & Image Proc, Monastir, Tunisia
[2] EFREI Cole Ingnieur Technol Informat & Commun, Paris, France
来源：
2019 15TH INTERNATIONAL CONFERENCE ON SEMANTICS, KNOWLEDGE AND GRIDS (SKG 2019) | 2019年
关键词：
Labeled Petri Nets; Minimum Initial Marking; Label sequence; GRASP algorithms;
D O I：
10.1109/SKG49510.2019.00021
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Computing the minimum initial marking (MIM) in labeled Petri nets (PN) while considering a sequence of labels constitutes a difficult problem. The existing solutions of such a problem suffer from diverse limitations. In this paper, we proposed a new approach to automatically compute the MIM in labeled PNs in a timely fashion. We adopted a grasp (Greedy Randomized Adaptive Search Procedure)-based algorithm to model the MIM problem. The choice of such an algorithm is justified by the nature of the MIM process which belongs to the NP-hard class. We experimentally showed the effectiveness of our approach and empirically studied the initial marking quality in particular.
引用
收藏
页码：75 / 80
页数：6
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