利用广义 Petri 网和高度知情的启发式搜索安排 AMS

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
FengLian Yuan , Bo Huang , JianYong Lv , MeiJi Cui
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引用次数: 0

摘要

在基于 Petri 网(PN)的 A∗ 搜索中,启发式函数的设计对自动制造系统(AMS)的搜索效率和排程质量有很大影响。在 Luo 等人(2015 年)的研究中,为基于位置定时 PN 的 A∗ 搜索制定了两个可接受的启发式函数,以调度 AMS。为了拓宽其应用场景并提高搜索效率,本文提出了一种新的启发式函数,其计算考虑了实际 AMS 中经常遇到但通常不考虑的多资源获取、加权弧、冗余资源单元和过时资源。所提出的计算方法可以处理广义 PN,提供比普通 PN 更广泛的应用场景。此外,它还被证明是可接受的,并且比同类算法更有信息量,从而确保获得的计划是最优的,并使基于定时 PN 的 A∗ 搜索更有效率。为了验证所提方法的功效和效率,对几个基准系统进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scheduling AMSs with generalized Petri nets and highly informed heuristic search
The design of the heuristic function in a Petri-net(PN)-based A search significantly impacts search efficiency and schedule quality for automated manufacturing systems (AMSs). In Luo et al. (2015), two admissible heuristic functions were formulated for an A search based on place-timed PNs to schedule AMSs. To broaden its application scenarios and enhance search efficiency, this paper proposes a new heuristic function whose calculations take account of multiple resource acquisitions, weighted arcs, redundant resource units, and outdated resources, which are commonly encountered in practical AMSs but usually not considered. The proposed one can deal with generalized PNs, offering broader application scenarios than ordinary PNs. In addition, it is proven to be admissible and more informed than its counterparts, ensuring that the obtained schedules are optimal and making the timed PN-based A search more efficient. To validate the efficacy and efficiency of the proposed method, several benchmark systems are tested.
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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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