为资源分配系统配置最少资源的增强活泼性初始标记

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Sciences Pub Date : 2024-11-08 DOI:10.1016/j.ins.2024.121623
Yanxiang Feng , Sida Ren , Keyi Xing , Yikang Yang , MengChu Zhou
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引用次数: 0

摘要

对于资源分配系统(RAS)的 Petri 网模型来说,执行有效性至关重要。为 Petri 网植物建立一个初始标记,使其成为活网,是一件有趣但极具挑战性的事情。这种初始标记被称为活泼强化初始标记(LIM)。尽管现有文献介绍了各种 LIM,但还没有研究涉及如何最大限度地减少 LIM 中的资源数量。本研究的重点是为一类 Petri 网(即具有共享资源的连续系统(S4PRs))设计具有最少资源的 LIM(LIM-MR),方法是为每个资源位置分配一个标记容量,从而使所有涉及资源的总和最小化。这项工作首先为 S4PR 建立了一种必要且充分的有效性条件,然后将其编码为混合整数编程 (MIP) 公式中的一系列变量和约束条件。虽然 LIM-MR 不一定是唯一的,但通过求解所提出的 MIP 公式,可以为所考虑的 S4PR 得到至少一个 LIM-MR。实验结果表明了这种方法对 S4PR 的可解性。
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Configuration of liveness-enforcing initial marking with the minimum resources for resource allocation systems
The enforcement of liveness is crucial for Petri nets models of resource allocation systems (RASs). It is interesting yet very challenging to establish an initial marking for Petri net plants so that the net is live. Such an initial marking is referred to as liveness-enforcing initial marking (LIM). Despite existing literature presenting various LIMs, no studies have addressed the issue of minimizing the number of resources in an LIM. This work focuses on designing an LIM with the minimum resources (LIM-MR) for a class of Petri nets called systems of sequential systems with shared resources (S4PRs) by assigning a token capacity to each resource place, such that the sum of all involved resources is minimized. This work first establishes a kind of necessary and sufficient liveness condition for S4PR, which is then encoded into a series of variables and constraints in a mixed-integer programming (MIP) formulation. Although LIM-MR may not be unique, solving the proposed MIP formulation can obtain at least one LIM-MR for S4PR under consideration. The experimental results show the solvability of this approach for S4PRs.
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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