Heat Treatment Process Parameter Estimation using Heuristic Optimization Algorithms

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@InProceedings{4777,
  author =       "Michael Kommenda and Bogdan Burlacu and 
                 Reinhard Holecek and Andreas Gebeshuber and 
                 Michael Affenzeller",
  title =        "Heat Treatment Process Parameter Estimation using
                 Heuristic Optimization Algorithms",
  booktitle =    "Proceedings of the 27th European Modeling and
                 Simulation Symposium EMSS 2015",
  year =         "2015",
  pages =        "222--228",
  address =      "Bergeggi, Italy",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.msc-les.org/proceedings/emss/2015/EMSS2015_222.pdf",
  size =         "6 pages",
  abstract =     "We present an approach for estimating control
                 parameters of a plasma nitriding process, so that
                 materials with desired product qualities are created.
                 We achieve this by solving the inverse optimization
                 problem of finding the best combination of parameters
                 using a real-vector optimization algorithm, such that
                 multiple regression models evaluated with a concrete
                 parameter combination predict the desired product
                 qualities simultaneously.

                 The results obtained on real-world data of the
                 nitriding process demonstrate the effectiveness of the
                 presented methodology. Out of various regression and
                 optimization algorithms, the combination of symbolic
                 regression for creating prediction models and covariant
                 matrix adaptation evolution strategies for estimating
                 the process parameters works particularly well. We
                 discuss the influence of the concrete regression
                 algorithm used to create the prediction models on the
                 parameter estimations and the advantages, as well as
                 the limitations and pitfalls of the methodology.",
}

Genetic Programming entries for Michael Kommenda Bogdan Burlacu Reinhard Holecek Andreas Gebeshuber Michael Affenzeller

Citations