Deriving Inventory Control Policies for Periodic Review with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{kleinau:2003:OR,

• author = "Peer Kleinau and Ulrich Thonemann",
• title = "Deriving Inventory Control Policies for Periodic Review with Genetic Programming",
• booktitle = "International Conference on Operations Research, OR 2003",
• year = "2003",
• editor = "Dino Ahr and Roland Fahrion and Marcus Oswald and Gerhard Reinelt",
• pages = "87--94",
• address = "Heidelberg",
• month = "3-5 " # sep,
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, Inventory",
• isbn13 = "978-3-540-21445-8",
• DOI = "doi:10.1007/978-3-642-17022-5_12",
• abstract = "In Germany, inventories are estimated to be worth of more than 500 billion euros. 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 optimisation problems. In this paper, we show how closed-form heuristics for a common inventory-control setting with periodic review can be found with GP.",
• notes = "Wednesday, Sep. 3, 2003, 16:45 - 18:45, Room: NU 05 (see p. 41 for session)",

}

Genetic Programming entries for Peer Kleinau Ulrich Thonemann

Citations