An Intelligent Scheduling Method Based on Flow Control

Abstract

The invention discloses an intelligent scheduling method based on flow control. The specific steps of the intelligent scheduling method based on flow control are as follows: S1: Initialization: 1.1 Receive task instructions from the central scheduling system; 1.2 Assign priority to workstations assigned by the scheduling system Sorting; 1.3 Select the idle AGV closest to the required task shelf; S2: Detection density and flow control: 2.1 Calculate the global area as A; 2.2 Define i as the index of path area segmentation, and the base is 2. This method uses a binary logarithmic backoff mechanism to control the flow of AGVs in transit, reduce the pressure of task flow on path resources, maintain a balanced overall distribution, make paths use opportunities equal, and avoid path conflicts and road resource competition during peak hours. On the premise of guaranteeing timeliness processing of order tasks, the present invention adopts partitioned phased flow control, reduces path congestion rate, improves transportation efficiency, and reduces the probability of AGV congestion and collision.

Description

technical field [0001] The invention relates to the technical field of logistics scheduling, in particular to an intelligent scheduling method based on flow control. Background technique [0002] In the logistics industry, the commonly used control mode for unmanned warehouses is the central control system. For the B-type goods-to-person mode, the AGV scheduling system is commonly used to distribute orders from WMS (Warehouse Management System). The AGV scheduling system is located between the central control system (CCS) and the underlying control system (WCS). In business scenarios, route resources and robot car resources are limited, but tasks (Job) are constantly pouring in at any time, becoming a pool of more and more orders. Therefore, the scheduling system should not only consider the fairness of the use of path resources, so that as many AGVs as possible can get access to the road, but also consider the throughput of system tasks to increase the transmission rate as...

AI Technical Summary

Problems solved by technology

[0004] (1) The utilization rate of workstations is unbalanced, and the degree of busyness of each workstation varies;

[0005] (2) The AGV is far away from the task, resulting in an increase in path cost;

[0006] (3) The scheduling rate of AGVs is unbalanced, and the degree of busyness of each AGV varies;

[0007] (4) The flow control is not timely, causing multiple AGVs to compete to share the intersection, increasing the risk of congestion

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