Acquisition of approximate throughput formulas for serial production lines with parallel machines using intelligent techniques
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{boulas_acquisition_2018,
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address = "Rio Patras, Greece",
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title = "Acquisition of approximate throughput formulas for
serial production lines with parallel machines using
intelligent techniques",
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isbn13 = "978-1-4503-6433-1",
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URL = "http://dl.acm.org/citation.cfm?doid=3200947.3201028",
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DOI = "doi:10.1145/3200947.3201028",
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abstract = "Estimating the performance of a production line is a
difficult problem because of the enormous number of
states that exist when analysing such systems. In
addition to the methods developed to address the
problem, it is very useful to have a formula linking
the characteristics of the line to its performance.
Three cases of sort serial production lines with
parallel and identical machines in each workstation are
examined in this paper. By using a combinational method
that applies genetic programming (GP) and an innovative
nature inspired method, named sonar inspired
optimization (SIO) to improve the results, three models
are derived to obtain the throughput of the
corresponding lines. Further work will take place
because results derived in this paper are
encouraging.",
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language = "en",
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booktitle = "Proceedings of the 10th {Hellenic} {Conference} on
{Artificial} {Intelligence}",
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publisher = "ACM Press",
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author = "Konstantinos Boulas and Alexandros Tzanetos and
Georgios Dounias",
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month = jul,
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year = "2018",
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note = "Article No 18",
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keywords = "genetic algorithms, genetic programming,
parallel-machine stations, performance evaluation,
serial production lines, Sonar Inspired Optimization",
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pages = "18:1--18:7",
- }
Genetic Programming entries for
Konstantinos Boulas
Alexandros Tzanetos
Georgios Dounias
Citations