Deriving simple (R,T)-policies with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Peer Kleinau",
  title =        "Deriving simple (R,T)-policies with Genetic
  booktitle =    "Fifth metaheuristics conference, MIC2003",
  year =         "2003",
  editor =       "Toshihide Ibaraki",
  address =      "Kyoto, Japan",
  month =        "25-28 " # aug,
  keywords =     "genetic algorithms, genetic programming,
                 inventory-control, (R,T)-policy",
  URL =          "",
  size =         "8 pages",
  abstract =     "In the US, inventories are estimated to be worth of
                 more than 1 trillion. To manage these inventories,
                 numerous inventory-control policies have been developed
                 in the last decades. These inventory-control policies
                 are typically derived analytically, which is often
                 complicated and time consuming. For many relevant
                 settings, such as complex multi-echelon models, there
                 exist no closed-form formulae to describe the optimal
                 solution. Optimal solutions for those problems are
                 determined by complex algorithms that require several
                 iteration steps. With Genetic Programming (GP) however,
                 inventory-control policies can be derived in a simple
                 manner. GP is an algorithm related to Genetic
                 Algorithms. It applies the principles of natural
                 evolution to solve optimization problems. In this
                 paper, we show how a simple closed-form heuristics for
                 a common inventory-control setting can be derived with
                 GP. We focus on a simple (R,T)-policy to demonstrate
                 the capabilities of GP.",
  notes =        "published on CD-ROM. Selected papers in special issue?
        broken Jan 2013

Genetic Programming entries for Peer Kleinau