Advanced scheduling methodologies for flexible manufacturing systems using Petri nets and heuristic search

This source preferred by Hongnian Yu

This data was imported from DBLP:

Authors: Reyes-Moro, A., Yu, H. and Kelleher, G.

http://www.informatik.uni-trier.de/~ley/db/conf/icra/icra2000.html

Journal: ICRA

Pages: 2398-2403

Publisher: IEEE

This data was imported from Scopus:

Authors: Moro, A.R., Yu, H. and Kelleher, G.

Journal: Proceedings - IEEE International Conference on Robotics and Automation

Volume: 3

Pages: 2398-2403

ISSN: 1050-4729

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 in 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.

The data on this page was last updated at 04:57 on May 24, 2019.