### Abstract

We consider the problem of stacking containers in a given set of stacks of fixed maximum capacity when the pick-up times are stochastic with unknown probability distributions. The goal is to minimize the expected number of times a container is picked up while it is not at the top of its stack. We formulate several algorithms under varying assumptions about the available knowledge about the pick-up-time distributions. We distinguish four qualitatively different settings: 1) we know nothing about the actual distributions, 2) we have point estimates of the means, 3) we have point estimates of means and variances, or 4) we have historical samples of actual pick-up times. For each assumption we propose one or more algorithms. We test the algorithms empirically in many different scenarios, considering both sequential and concurrent arrivals. Additionally, we consider the computational complexity and ease of use of each algorithm.

Original language | English |
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Title of host publication | Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems |

Editors | PN Suganthan, D Fogel |

Place of Publication | Piscataway, NJ |

Publisher | IEEE Society |

Pages | 25-32 |

Number of pages | 8 |

ISBN (Electronic) | 978-1-4673-5905-4 |

DOIs | |

Publication status | Published - 2013 |

Externally published | Yes |

Event | IEEE CIPLS, Singapore, Singapore - Piscataway, NJ, USA Duration: 16 Apr 2013 → 19 Apr 2013 |

### Publication series

Name | |
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Publisher | IEEE |

### Conference

Conference | IEEE CIPLS, Singapore, Singapore |
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Period | 16/04/13 → 19/04/13 |

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## Cite this

van Hasselt, H., & La Poutré, J. A. (2013). Stacking under uncertainty: We know how to predict, but how should we act? In PN. Suganthan, & D. Fogel (Eds.),

*Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems*(pp. 25-32). IEEE Society. https://doi.org/10.1109/CIPLS.2013.6595196