A Neuro-Dynamic Programming Approach to Retailer Inventory Management

نویسندگان

  • Benjamin Van Roy
  • Dimitri P. Bertsekas
  • Yuchun Lee
  • John N. Tsitsiklis
چکیده

We present a model of two-echelon retailer inventory systems, and we cast the problem of generating optimal control strategies into the framework of dynamic programming. We formulate two speci c case studies, for which the underlying dynamic programming problems involve thirty-three and forty-six state variables, respectively. Because of the enormity of these state spaces, classical algorithms of dynamic programming are inapplicable. To address these complex problems, we develop approximate dynamic programming algorithms. The algorithms are motivated by recent research in arti cial intelligence involving simulation{based methods and neural network approximations, and they are representative of algorithms studied in the emerging eld of neuro-dynamic programming. We assess performance of resulting solutions relative to optimized s{type (\order{up{to") policies, which are generally accepted as reasonable heuristics for the types of problems we consider. In both case studies, we are able to generate control strategies substantially superior to the heuristics, reducing inventory costs by approximately ten percent.

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تاریخ انتشار 1997