An Intelligent Algorithm for Distributed Unmanned Warehouse Location Recommendation Based on Star Topology

Abstract

The invention discloses a distributed unmanned warehouse position recommendation intelligent algorithm based on a star topology, specifically relates to the field of e-commerce, including classifying the degree of commodity sales, identifying available free positions and work site coordinates, and according to the midpoint of the work site The coordinates extend the square area, disperse the storage locations of hot-selling products and set non-hot-selling products at the adjacent points of the storage locations of hot-selling products, and build a new square star topology on this basis, and calculate multiple square star topologies The structure is composed of a network of intervals. The present invention extends and evenly distributes the warehouse locations by adopting patterns from the inside to the outside and from top to bottom, left and right, so that the shelves can avoid the conflict of shared path resources during operation, and ensure that multiple distributed shelves keep running synchronously, improving the Production efficiency, the location recommendation algorithm outputs the best unmanned warehouse product layout effect, and the optimized distributed star topology principle can help the location to achieve the best layout with high efficiency.

Description

technical field [0001] The present invention relates to the field of e-commerce, more specifically, the present invention relates to a distributed unmanned warehouse location recommendation intelligent algorithm based on a star topology. Background technique [0002] With the development of the e-commerce industry, logistics has made great progress. In the logistics industry, for the B-type goods-to-person picking mode, the common way for unmanned warehouses is to carry the shelves carrying goods on unmanned trucks AGV and move them to work. At the site, the goods listed in the order are manually selected. In the business scenario of unmanned warehouse goods to people, we need to consider several common storage locations and corresponding modes of work sites. (1) One storage location corresponds to one Work site; (2) multiple storage locations correspond to one work site; (3) multiple storage locations correspond to multiple work sites. [0003] In the current business scen...

AI Technical Summary

Problems solved by technology

For a certain proportion of hot-selling products, artificial experience estimation is often used to reserve idle storage locations and complete preliminary storage location planning. When the loaded shelves are in the state of mobile transportation, the physical location of the warehouse location is dynamic and constantly changing. If manual experience estimation rules are used, it will cause conflicts in route resources and congestion at work sites

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