Wolf Ketter's Publications

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Adaptive Pricing in Multi-Agent Supply Chain Markets using Economic Regimes

Alexander Hogenboom, Wolfgang Ketter, Jan van Dalen, Uzay Kaymak, John Collins, and Alok Gupta. Adaptive Pricing in Multi-Agent Supply Chain Markets using Economic Regimes. In Conference on Information Systems and Technology (CIST 2009), October 2009.

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Abstract

Today's complex supply chain markets require adaptive product pricing. We propose a product pricing approach which assumes a double-bounded log-logistic distribution to be underlying offer prices, the parameters of which are estimated in real-time using Radial Basis Function Networks, based on available information. The relations between price distributions and available information are dynamically modeled, using economic regimes (characterizing market conditions) and error terms (accounting for customer feedback). Given the parametric approximations of price distributions, acceptance probabilities are estimated using a closed-form mathematical expression, which is used to determine the price yielding a desired quota. We implement our novel approach in the MinneTAC agent and test it against a price-following approach in the TAC SCM game. When competing against world's leading TAC SCM agents, performance significantly improves; bid efficiency increases and profits more than double.

@inproceedings{AHogenboom09CIST,
  author =       {Alexander Hogenboom and Wolfgang Ketter and Jan van Dalen and Uzay Kaymak and John Collins and Alok Gupta},
  title =        {{Adaptive Pricing in Multi-Agent Supply Chain Markets using Economic Regimes}},
  booktitle =    {{Conference on Information Systems and Technology (CIST 2009)}},
  year =         {2009},
  month =        {October},
  abstract =     {{Today's complex supply chain markets require adaptive
  product pricing. We propose a product pricing approach which assumes a
  double-bounded log-logistic distribution to be underlying offer prices, the
  parameters of which are estimated in real-time using Radial Basis Function
  Networks, based on available information. The relations between price
  distributions and available information are dynamically modeled, using
  economic regimes (characterizing market conditions) and error terms
  (accounting for customer feedback). Given the parametric approximations of
  price distributions, acceptance probabilities are estimated using a
  closed-form mathematical expression, which is used to determine the price
  yielding a desired quota. We implement our novel approach in the MinneTAC
  agent and test it against a price-following approach in the TAC SCM game.
  When competing against world's leading TAC SCM agents, performance
  significantly improves; bid efficiency increases and profits more than
  double.}},
  bib2html_pubtype = {Refereed Conference},
  bib2html_rescat = {Trading Agents: Supply-Chain Management},
}

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