Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab

Yinzhi Zhou; Kan Wu

doi:10.1109/ICIS.2017.7960099

Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab

Yinzhi Zhou
, Kan Wu

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

This paper presents an efficient algorithm for diffusion scheduling in a semiconductor fab. The diffusion area commonly creates long queue time in the entire process flow. Due to the complex constraints, such as parallel batching and time windows, and large solution space, it is difficult to find a feasible schedule in a timely manner. A greedy randomized procedure forms the batches. A heuristic method is introduced to handle the time window constraints. Two important properties of the problem are identified and applied to improve the quality of the solution. Simulated annealing is used as a local search procedure. Compared with the real schedule in the fab, the proposed algorithm can increase the effective moves significantly without violating queue time constraints.

Original language	English
Title of host publication	Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
Editors	Xiaohui Cui, Shaowen Yao, Simon Xu, Guobin Zhu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	785-789
Number of pages	5
ISBN (Electronic)	9781509055074
DOIs	https://doi.org/10.1109/ICIS.2017.7960099
State	Published - 27 06 2017
Externally published	Yes
Event	16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017 - Wuhan, China Duration: 24 05 2017 → 26 05 2017

Publication series

Name	Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017

Conference

Conference	16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017
Country/Territory	China
City	Wuhan
Period	24/05/17 → 26/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Furnace scheduling
Greedy randomized solution
Simulated annealing
Time window constraints

Access to Document

10.1109/ICIS.2017.7960099

Cite this

Zhou, Y., & Wu, K. (2017). Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab. In X. Cui, S. Yao, S. Xu, & G. Zhu (Eds.), Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017 (pp. 785-789). Article 7960099 (Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIS.2017.7960099

Zhou, Yinzhi ; Wu, Kan. / Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab. Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. editor / Xiaohui Cui ; Shaowen Yao ; Simon Xu ; Guobin Zhu. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 785-789 (Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017).

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abstract = "This paper presents an efficient algorithm for diffusion scheduling in a semiconductor fab. The diffusion area commonly creates long queue time in the entire process flow. Due to the complex constraints, such as parallel batching and time windows, and large solution space, it is difficult to find a feasible schedule in a timely manner. A greedy randomized procedure forms the batches. A heuristic method is introduced to handle the time window constraints. Two important properties of the problem are identified and applied to improve the quality of the solution. Simulated annealing is used as a local search procedure. Compared with the real schedule in the fab, the proposed algorithm can increase the effective moves significantly without violating queue time constraints.",

keywords = "Furnace scheduling, Greedy randomized solution, Simulated annealing, Time window constraints",

author = "Yinzhi Zhou and Kan Wu",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

year = "2017",

month = jun,

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doi = "10.1109/ICIS.2017.7960099",

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series = "Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Zhou, Y & Wu, K 2017, Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab. in X Cui, S Yao, S Xu & G Zhu (eds), Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017., 7960099, Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017, Institute of Electrical and Electronics Engineers Inc., pp. 785-789, 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017, Wuhan, China, 24/05/17. https://doi.org/10.1109/ICIS.2017.7960099

Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab. / Zhou, Yinzhi; Wu, Kan.
Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. ed. / Xiaohui Cui; Shaowen Yao; Simon Xu; Guobin Zhu. Institute of Electrical and Electronics Engineers Inc., 2017. p. 785-789 7960099 (Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wu, Kan

PY - 2017/6/27

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N2 - This paper presents an efficient algorithm for diffusion scheduling in a semiconductor fab. The diffusion area commonly creates long queue time in the entire process flow. Due to the complex constraints, such as parallel batching and time windows, and large solution space, it is difficult to find a feasible schedule in a timely manner. A greedy randomized procedure forms the batches. A heuristic method is introduced to handle the time window constraints. Two important properties of the problem are identified and applied to improve the quality of the solution. Simulated annealing is used as a local search procedure. Compared with the real schedule in the fab, the proposed algorithm can increase the effective moves significantly without violating queue time constraints.

AB - This paper presents an efficient algorithm for diffusion scheduling in a semiconductor fab. The diffusion area commonly creates long queue time in the entire process flow. Due to the complex constraints, such as parallel batching and time windows, and large solution space, it is difficult to find a feasible schedule in a timely manner. A greedy randomized procedure forms the batches. A heuristic method is introduced to handle the time window constraints. Two important properties of the problem are identified and applied to improve the quality of the solution. Simulated annealing is used as a local search procedure. Compared with the real schedule in the fab, the proposed algorithm can increase the effective moves significantly without violating queue time constraints.

KW - Furnace scheduling

KW - Greedy randomized solution

KW - Simulated annealing

KW - Time window constraints

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DO - 10.1109/ICIS.2017.7960099

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BT - Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017

A2 - Cui, Xiaohui

A2 - Yao, Shaowen

A2 - Xu, Simon

A2 - Zhu, Guobin

PB - Institute of Electrical and Electronics Engineers Inc.

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Zhou Y, Wu K. Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab. In Cui X, Yao S, Xu S, Zhu G, editors, Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 785-789. 7960099. (Proceedings - 16th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2017). doi: 10.1109/ICIS.2017.7960099

Heuristic simulated annealing approach for diffusion scheduling in a semiconductor Fab

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Keywords

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