Wolf Ketter's Publications

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Economic Regime Identification and Prediction in TAC SCM Using Sales and Procurement Information

Frederik Hogenboom, Wolfgang Ketter, Jan van Dalen, Uzay Kaymak, John Collins, and Alok Gupta. Economic Regime Identification and Prediction in TAC SCM Using Sales and Procurement Information. In Workshop: Trading Agent Design and Analysis (TADA) at Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009), pp. 25–34, July 2009.

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Abstract

Our research is focused on the effects of the addition of procurement information (offer prices) to a sales-based economic regime model. This model is used for strategic, tactical, and operational decision making in dynamic supply chains. We evaluate the performance of the regime model through experiments with the MinneTAC trading agent, which competes in the TAC SCM game. The new regime model has an overall predictive performance which is equal to the performance of the existing model. Regime switches are predicted more accurately, whereas the prediction accuracy of dominant regimes does not improve. However, because procurement information has been added to the model, the model has been enriched, which gives new opportunities for applications in the procurement market, such as procurement reserve pricing.

BibTeX

@INPROCEEDINGS{FHogenboom09TADA,
  AUTHOR =       {Frederik Hogenboom and Wolfgang Ketter and Jan van Dalen and Uzay Kaymak and John Collins and Alok Gupta},
  TITLE =        {{Economic Regime Identification and Prediction in TAC SCM Using Sales and Procurement Information}},
  BOOKTITLE =    {{Workshop: Trading Agent Design and Analysis (TADA) at Twenty-First International Joint Conference on Artificial Intelligence (IJCAI 2009)}},
  YEAR =         {2009},
  pages =        {25--34},
  month =        {July},
  abstract =     {{Our research is focused on the effects of the addition of
  procurement information (offer prices) to a sales-based economic regime
  model. This model is used for strategic, tactical, and operational decision
  making in dynamic supply chains. We evaluate the performance of the regime
  model through experiments with the MinneTAC trading agent, which competes in
  the TAC SCM game. The new regime model has an overall predictive performance
  which is equal to the performance of the existing model. Regime switches are
  predicted more accurately, whereas the prediction accuracy of dominant
  regimes does not improve. However, because procurement information has been
  added to the model, the model has been enriched, which gives new
  opportunities for applications in the procurement market, such as procurement
  reserve pricing.}},
  bib2html_pubtype = {Refereed Workshop/Symposium},
  bib2html_rescat = {Trading Agents: Supply-Chain Management},
}

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