Predicitve Decision Models for an Energy Efficient Operation of Stacker Cranes in a High-bay Warehouse

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Beitragende

Abstract

This paper presents a simulation-based optimization framework to find and evaluate optimal storage plans in a high-bay warehouse. The two objectives under consideration are reducing the total energy consumption and maximizing the recuperation of energy of stacker cranes. These cranes operating in different aisles are connected by an internal circuit. One part of the framework simulates the power flows both on a single stacker crane and in the internal circuit. Based on that, the optimization part computes energy optimal trajectories for prescribed movements using a variational approach. By dividing the trajectories into time intervals, a mixed-integer programming (MIP) model delivers double-cycle plans. For longer down movements the shape of optimal trajectories would be technically disadvantageous which requires alternatives to avoid the abrasion of the devices.

Details

OriginalspracheEnglisch
Titel2024 Winter Simulation Conference, WSC 2024
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers (IEEE)
Seiten1634-1644
Seitenumfang11
ISBN (elektronisch)979-8-3315-3420-2
ISBN (Print)979-8-3315-3421-9
PublikationsstatusVeröffentlicht - Jan. 2025
Peer-Review-StatusJa

Publikationsreihe

ReiheProceedings - Winter Simulation Conference
ISSN0891-7736

Konferenz

TitelWinter Simulation Conference 2024
UntertitelSimulation for the Imagination Age: Unlocking the Value of Imagination with Simulation
KurztitelWSC 2024
Dauer15 - 18 Dezember 2024
Webseite
OrtOrlando World Center Marriott
StadtOrlando
LandUSA/Vereinigte Staaten

Externe IDs

ORCID /0000-0002-6691-5030/work/229893311
ORCID /0000-0002-1484-7187/work/229893385

Schlagworte