Design of dynamic scheduling strategy for metering equipment in warehouse environment based on intelligent algorithm

In the operation of storage system, improper scheduling of shuttle and hoist will waste resources and affect the picking efficiency, so it is of great significance to optimize the operation scheduling of storage system.Based on queuing theory, this paper constructs a queuing model of ring RGV system and proposes queuing model assumptions of hoist system to analyze the reasonableness of storage layout.The operation activity scheduling mechanism is designed to execute the warehousing activities strictly in accordance with the established operation order.Agree on the ring track RGV operation rules, calculate the distance between any two points on the track, and ensure the shortest distance of the warehousing operation.Merge the shortest operation path and the shuttle car operation equilibrium rules to construct a dynamic scheduling decision model.Through the storage resources in and out of storage management and scheduling module, improve the measuring equipment intelligent storage system, apply the system to the actual storage operations, analyze the operational efficiency.After the implementation of the strategy proposed in this paper, the optimal scheduling result is 36min, the execution time of different types of work is different, and the operation time of equipment J1-J4 is 15min, 23min, 17min, 34min respectively.The pickup execution efficiency of the strategy used in this paper is improved by 66.38%, and the pickup efficiency is improved by 10% when the number of equipment is less than 300 pieces.The scheduling strategy proposed in this paper has a higher priority when facing a small number of devices.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-03-30
DOI
https://doi.org/10.61091/jcmcc127a-511
Primary Topic
Industrial Automation and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Design of dynamic scheduling strategy for metering equipment in warehouse environment based on intelligent algorithm

Journal of Combinatorial Mathematics and Combinatorial Computing
Industrial Automation and Control Systems
article

Design of dynamic scheduling strategy for metering equipment in warehouse environment based on intelligent algorithm

article en

Abstract

In the operation of storage system, improper scheduling of shuttle and hoist will waste resources and affect the picking efficiency, so it is of great significance to optimize the operation scheduling of storage system.Based on queuing theory, this paper constructs a queuing model of ring RGV system and proposes queuing model assumptions of hoist system to analyze the reasonableness of storage layout.The operation activity scheduling mechanism is designed to execute the warehousing activities strictly in accordance with the established operation order.Agree on the ring track RGV operation rules, calculate the distance between any two points on the track, and ensure the shortest distance of the warehousing operation.Merge the shortest operation path and the shuttle car operation equilibrium rules to construct a dynamic scheduling decision model.Through the storage resources in and out of storage management and scheduling module, improve the measuring equipment intelligent storage system, apply the system to the actual storage operations, analyze the operational efficiency.After the implementation of the strategy proposed in this paper, the optimal scheduling result is 36min, the execution time of different types of work is different, and the operation time of equipment J1-J4 is 15min, 23min, 17min, 34min respectively.The pickup execution efficiency of the strategy used in this paper is improved by 66.38%, and the pickup efficiency is improved by 10% when the number of equipment is less than 300 pieces.The scheduling strategy proposed in this paper has a higher priority when facing a small number of devices.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Industry, innovation and infrastructure
Openalex Percentile: Top 91%
Industrial Automation and Control Systems
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