Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Multiple RGV dynamic scheduling method based on genetic algorithm

A genetic algorithm and dynamic scheduling technology, applied in the field of multi-RGV dynamic scheduling based on genetic algorithm, can solve problems such as reduced transportation efficiency, RGV congestion, limited transportation capacity, etc., to improve transportation efficiency, reduce congestion and empty runs, and expand applications range effect

Active Publication Date: 2012-09-12
合肥庐阳科技创新集团有限公司
View PDF4 Cites 27 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The delivery capacity of the first two conveying systems is limited and cannot meet the actual needs of large material flow
[0004] The third method has relatively large transportation capacity, but how to reasonably dispatch each RGV is more complicated
This strategy can work well when the logistics volume is small, that is, the number of RGVs is more than the number of incoming and outgoing tasks most of the time. When the logistics volume is large, that is, the number of RGVs is mostly small Due to the number of inbound and outbound tasks and new inbound and outbound tasks are constantly being generated, congestion or empty runs due to unreasonable scheduling of RGVs will be prominent, and the delivery efficiency will be greatly reduced

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multiple RGV dynamic scheduling method based on genetic algorithm
  • Multiple RGV dynamic scheduling method based on genetic algorithm
  • Multiple RGV dynamic scheduling method based on genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] see figure 1 , the RGV 5 in the present embodiment is L RGVs running in a one-way cycle on the circular track 8 of the automatic three-dimensional warehouse conveying system; figure 1 In the shown automatic three-dimensional warehouse, each incoming conveyor belt 1, outgoing conveyor belt 2, multi-layer shelf 3 and stacker 4 are arranged sequentially along one side of the circular track, and on the other side of the circular track along the line. Arrange the incoming goods platform 6, the picking platform 7, the external material delivery tool 9 and the outgoing platform 10; in this embodiment, it is stipulated that each RGV can only transport one outgoing task or incoming goods task at a time, and the dynamic scheduling method of each RGV is Proceed as follows:

[0042] The first step is to take out the first Q incoming and outgoing tasks according to the requirements for all the K incoming and outgoing goods tasks that have been generated and are waiting to be shippe...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a multiple RGV dynamic scheduling method based on a genetic algorithm. The method is characterized by: aiming at a dynamic scheduling problem of multiple RGVs (rail guided vehicle) on a circular track in an automatic stereoscopic warehouse conveying system, using the genetic algorithm to establish a model and solve so as to obtain an optimization scheme which can achieve a task of scheduling the multiple RGVs to convey goods. Therefore, conveying efficiency of the RGVs can be greatly increased. Simultaneously, aiming at a concrete problem, a practical coding method is provided so that an application scope of the genetic algorithm can be expanded.

Description

technical field [0001] The invention relates to a genetic algorithm-based multi-RGV dynamic scheduling method, which is applied to the dynamic scheduling problem of multiple RGVs in an automatic three-dimensional warehouse transportation system under large material flow. Background technique [0002] Automated three-dimensional warehouse AS / RS is a modern storage device, generally composed of a central control system, multi-layer shelves, stackers, conveying systems, external material delivery tools, etc. In the conveying system, there are multiple RGVs running on a predetermined track (usually a rail or alloy track), responsible for transporting materials distributed around the track on the picking platform, the loading and unloading platform, and the loading and unloading conveyor belt to complete the multi-layer shelf import and export tasks. Among them, the picking platform, the loading and unloading platform connects the track and the external material delivery tool, t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08G06N3/12
Inventor 吴焱明赵韩刘永强
Owner 合肥庐阳科技创新集团有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com