Route-optimization Based Storage Allocation Algorithm in Intelligent High-bay Warehouses

The shuttle-carrier warehouse is a new kind of high-density intelligent high-bay warehouse. Based on existing research, the storage allocation problem of this intelligent highbay warehouse has been studied, and an improved dynamic programming algorithm has been proposed based on the idea of route se...

Full description

Saved in:
Bibliographic Details
Published in:2021 4th International Conference on Intelligent Autonomous Systems (ICoIAS) pp. 240 - 245
Main Authors: Huang, Qiubo, Ye, Yuxiang, Zhu, Zhenwei, Lu, Ting
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2021
Subjects:
Computational efficiency
Computational modeling
device busy level variance
Dynamic programming
Heuristic algorithms
high-bay warehouse
Linear programming
Power demand
Resource management
route- optimization
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The shuttle-carrier warehouse is a new kind of high-density intelligent high-bay warehouse. Based on existing research, the storage allocation problem of this intelligent highbay warehouse has been studied, and an improved dynamic programming algorithm has been proposed based on the idea of route selection. The objective function designed in this paper mainly considers the "task completion time" and the "device busy level variance" for the multiple pallets of multiple tasks which will be allocated into the warehouse. The "task completion time" allows the algorithm to allocate the storage locations according to the current state of the warehouse and the optimized route, thus reducing the time to complete all tasks. A smaller "device busy level variance" allows the workload of the device to be well balanced, avoiding some devices being too busy and causing excessive devices' loss or rapid power consumption. Through simulation experiments, the improved algorithm reduces the "task completion time" by 36.5% and the average "device busy level variance" by 14.5% compared to the unimproved algorithm.
DOI:10.1109/ICoIAS53694.2021.00050