| In Germany, inventories are estimated to be worth of
more than 500 billion $. To manage these inventories,
numerousinventory-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-echelonmodels, 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 closed-formheuristics for a common
inventory-control setting with periodic review can be
found with GP.",
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