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Content Provider | IEEE Xplore Digital Library |
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Author | Moro, A.R. Yu, H. Kelleher, G. |
Copyright Year | 2000 |
Description | Author affiliation: Sch. of Comput. & Math. Sci., Liverpool John Moores Univ., UK (Moro, A.R.) |
Abstract | The combination of Petri net (PN) and AI to solve flexible manufacturing systems (FMS) scheduling problems has been proven to be a promising approach. However, the NP-hard nature of the problem prevents the PN capability of reasoning about the behavior of a practical system. To overcome this drawback, we propose two techniques: a systematic method to avoid the generation of unpromising paths within the search graph, and a stage-search based algorithm. The algorithm developed is based on the application of the A* algorithm and the PN-based heuristics. The search is performed within a limited local search window where an optimization policy is applied to evaluate the most promising paths. For each state, the algorithm is able to decide whether an enabled operation is applied, and to maintain the decision until new system information makes the reconsideration meaningful. Comparison with previous work is presented to show the superiority of the proposed approach. |
Starting Page | 2398 |
Ending Page | 2403 |
File Size | 606308 |
Page Count | 6 |
File Format | |
ISBN | 0780358864 |
ISSN | 10504729 |
DOI | 10.1109/ROBOT.2000.846386 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2000-04-24 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Job shop scheduling Flexible manufacturing systems Petri nets Processor scheduling Space exploration Artificial intelligence Control systems Job production systems Scheduling algorithm Mathematical model |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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