## Abstract

One of the most important policies adopted in inventory control is the replenishment cycle policy. Such a policy provides an effective means of dampening planning instability and coping with demand uncertainty. We describe a constraint programming approach for computing optimal replenishment cycle policy parameters under non-stationary stochastic demand, ordering, holding and shortage costs. Our solution approach exploits the convexity of the cost-function to dynamically compute during search the cost associated with a given decision variable assignment. By using our

model we gauge the quality of an existing approximate mixed integer linear programming approach that exploits a piecewise linear approximation for the complex cost function. Furthermore, our computational experience shows that our approach can solve realistic instances in a fraction of a second.

model we gauge the quality of an existing approximate mixed integer linear programming approach that exploits a piecewise linear approximation for the complex cost function. Furthermore, our computational experience shows that our approach can solve realistic instances in a fraction of a second.

Original language | English |
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Title of host publication | Proceedings of the Toulouse Global Optimization workshop (TOGO 2010) |

Subtitle of host publication | ENSEEIHT and Ecole Polytechnique |

Pages | 137 |

Number of pages | 140 |

Publication status | Published - 2010 |

Event | Toulouse Global Optimization workshop (TOGO 2010) - Toulouse, France Duration: 31 Aug 2010 → 3 Sep 2010 |

### Conference

Conference | Toulouse Global Optimization workshop (TOGO 2010) |
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Country/Territory | France |

City | Toulouse |

Period | 31/08/10 → 3/09/10 |