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Accession number:


20161102092737
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Accession number:


20161102092737






Title:

On-line scheduling of cluster tools based on hybrid quantum evolutionary algorithm






Authors:

Li, Linying1 ; Lu, Rui2





Author affiliation:

1School of Software, Dalian University of Foreign Languages, Dalian, Liaoning Provice, China






2Police Information Department, Liaoning Police College, Dalian, Liaoning Provice, China






Source title:

2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics






Abbreviated source title:

IEEE Int. Conf. Inf. Autom., ICIA - conjunction IEEE Int. Conf. Autom. Logist.






Monograph title:

2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics






Issue date:

September 28, 2015






Publication year:

2015






Pages:

2558-2562






Article number:

7279716






Language:

English






ISBN-13:

9781467391047






Document type:

Conference article (CA)






Conference name:

2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics






Conference date:

August 8, 2015 - August 10, 2015






Conference location:

Yunnan, China






Conference code:

116345






Sponsor:

CAS Shenzhen Institute of Advanced Technology; Harbin Institute of Technology Shenzhen Graduate School; HIT State Key Laboratory of Robotics and Systems; IEEE Robotics and Automation Society; Shanghai Gaitech Scientific Instruments Co., Ltd.; The Chinese University of Hong Kong






Publisher:

Institute of Electrical and Electronics Engineers Inc.






Abstract:

For on-line scheduling problem of cluster tools in semiconductor manufactory, this paper proposes an on-line scheduling method based on hybrid quantum evolutionary algorithm. This method determines the optimal wafer sequence by quantum evolutionary, while the heuristic algorithm determines the robot sequence based on the given sequence by two-stage recursion procedure. One recursion procedure is to search the feasible solution space of a new insert wafer in a forward stepwise manner, which guarantees both logic correctness and temporal constraints. The other computes the optimal solution among the feasible solution space obtained in the previous phase in a maximum backtracking manner. The simulations show that the mentioned method is effective for solving the large-scale scheduling problems. © 2015 IEEE.






Number of references:

11






Main heading:

Evolutionary algorithms






Controlled terms:

Algorithms - Automation - Clustering algorithms - Heuristic algorithms - Heuristic methods - Optimization - Scheduling - Silicon wafers - Tools






Uncontrolled terms:

Cluster tool - Feasible solution spaces - Large-scale scheduling problems - Online scheduling - Optimal solutions - Quantum evolutionary algorithms - Recursions - Temporal constraints






Classification code:

714.2 Semiconductor Devices and Integrated Circuits - 723.1 Computer Programming - 731 Automatic Control Principles and Applications - 903.1 Information Sources and Analysis - 912.2 Management - 921.5 Optimization Techniques





DOI:

10.1109/ICInfA.2015.7279716






Database:

Compendex






Compilation and indexing terms, © 2016 Elsevier Inc.
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