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
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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
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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 -