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Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach. / Hildebrandt, Torsten; Heger, Jens; Scholz-Reiter, Bernd.
Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. New York: Association for Computing Machinery, Inc, 2010. p. 257-264.

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Hildebrandt, T, Heger, J & Scholz-Reiter, B 2010, Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach. in Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. Association for Computing Machinery, Inc, New York, pp. 257-264, 12th Annual Genetic and Evolutionary Computation Conference - 2010, Portland, Oregon, United States, 07.07.10. https://doi.org/10.1145/1830483.1830530

APA

Hildebrandt, T., Heger, J., & Scholz-Reiter, B. (2010). Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach. In Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 (pp. 257-264). Association for Computing Machinery, Inc. https://doi.org/10.1145/1830483.1830530

Vancouver

Hildebrandt T, Heger J, Scholz-Reiter B. Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach. In Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. New York: Association for Computing Machinery, Inc. 2010. p. 257-264 doi: 10.1145/1830483.1830530

Bibtex

@inbook{1c5ce7449de54ac7aba4a66fcdd25bf4,
title = "Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach",
abstract = "Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and objectives automatic rule search mechanism are investigated. In this paper an approach using Genetic Programming (GP) is presented. The priority rules generated by GP are evaluated on dynamic job shop scenarios from literature and compared with manually developed rules yielding very promising results also interesting for Simulation Optimization in general.",
keywords = "Dispatching rules, Genetic programming, Job shop scheduling, Stochastic system optimization, Engineering",
author = "Torsten Hildebrandt and Jens Heger and Bernd Scholz-Reiter",
year = "2010",
doi = "10.1145/1830483.1830530",
language = "English",
isbn = "978-1-4503-0072-8",
pages = "257--264",
booktitle = "Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10",
publisher = "Association for Computing Machinery, Inc",
address = "United States",
note = "12th Annual Genetic and Evolutionary Computation Conference - 2010, 12th Annual GECCO - 2010 ; Conference date: 07-07-2010 Through 11-07-2010",
url = "http://www.sigevo.org/gecco-2010/",

}

RIS

TY - CHAP

T1 - Towards improved dispatching rules for complex shop floor scenarios - A genetic programming approach

AU - Hildebrandt, Torsten

AU - Heger, Jens

AU - Scholz-Reiter, Bernd

N1 - Conference code: 12

PY - 2010

Y1 - 2010

N2 - Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and objectives automatic rule search mechanism are investigated. In this paper an approach using Genetic Programming (GP) is presented. The priority rules generated by GP are evaluated on dynamic job shop scenarios from literature and compared with manually developed rules yielding very promising results also interesting for Simulation Optimization in general.

AB - Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and objectives automatic rule search mechanism are investigated. In this paper an approach using Genetic Programming (GP) is presented. The priority rules generated by GP are evaluated on dynamic job shop scenarios from literature and compared with manually developed rules yielding very promising results also interesting for Simulation Optimization in general.

KW - Dispatching rules

KW - Genetic programming

KW - Job shop scheduling

KW - Stochastic system optimization

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=77955890955&partnerID=8YFLogxK

U2 - 10.1145/1830483.1830530

DO - 10.1145/1830483.1830530

M3 - Article in conference proceedings

AN - SCOPUS:77955890955

SN - 978-1-4503-0072-8

SP - 257

EP - 264

BT - Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10

PB - Association for Computing Machinery, Inc

CY - New York

T2 - 12th Annual Genetic and Evolutionary Computation Conference - 2010

Y2 - 7 July 2010 through 11 July 2010

ER -

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Manufacturing of irregular shapes through force control in incremental sheet forming with active medium

Thiery, S., Zein El Abdine, M., Heger, J. & Ben Khalifa, N., 01.05.2025, In: Advances in Industrial and Manufacturing Engineering. 10, 11 p., 100157.

Research output: Journal contributions › Journal articles › Research › peer-review

Beschleunigte Erstellung von Simulationsmodellen für Produktions- und Logistikprozesse mithilfe von GPT-basierten Large Language Models

Krämer, R. & Heger, J., 01.09.2024, ASIM SST 2024 Tagungsband Kurzbeiträge: 27. ASIM Symposium Simulationstechnik, 4.9.-6.9.2024, Universität der Bundeswehr München. Rose, O. & Uhlig, T. (eds.). Wien: ARGESIM Verlag , p. 21 - 24 4 p. (ARGESIM Report; vol. 46)(ASIM Mitteilung; vol. 189).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Digitale Kontaktnachverfolgung bei Infektionskrankheiten: Projektstudie ZIL-Kontakt

Drews, P., Funk, B., Heger, J., Lehr, D., Zimmer, M. P. & Lemmer, K., 22.08.2024, Lüneburg: Leuphana Universität Lüneburg, 25 p.

Research output: Working paper › Project reports › Transfer

Increased Reliability of Draw-In Prediction in a Single Stage Deep-Drawing Operation via Transfer Learning

Wollschlaeger, L., Heinzel, C., Thiery, S., Abdine, M. Z. E., Khalifa, N. B. & Heger, J., 01.01.2024, In: Procedia CIRP. 130, p. 270-275 6 p.

Research output: Journal contributions › Conference article in journal › Research › peer-review

Neural network-based estimation and compensation of friction for enhanced deep drawing process control

Thiery, S., Zein El Abdine, M., Heger, J. & Ben Khalifa, N., 15.05.2024, Material Forming ESAFORM 2024: The 27th International ESAFORM Conference on Material Forming – ESAFORM 2024 – held in Toulouse (France), at the Pierre Baudis Convention Center between 24-26th April, 2024. Araujo, A. C., Cantarel, A., Chabert, F., Korycki, A., Olivier, P. & Schmidt, F. (eds.). Millersville: MaterialsResearchForum LLC, p. 1462-1471 10 p. 162. (Materials Research Proceedings; vol. 41).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

DOI

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