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A Dynamic Weighted Heuristic Scheduling Method for Automatic Manufacturing System

An automatic manufacturing system and heuristic scheduling technology, applied in the general control system, control/regulation system, program control, etc., can solve the problems that the automatic manufacturing system is not applicable and the depth cannot be predicted in advance, so as to speed up the calculation and analysis of the model , Accelerate the acquisition speed, and seek the effect of accelerating the acquisition speed

Active Publication Date: 2022-05-27
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

However, the DWA algorithm needs to estimate the depth of the final solution in advance, which is not suitable for automatic manufacturing systems with alternative routes
In the actual automatic manufacturing system, it is very common that the depth cannot be predicted in advance, and the existing methods cannot effectively solve this problem

Method used

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  • A Dynamic Weighted Heuristic Scheduling Method for Automatic Manufacturing System
  • A Dynamic Weighted Heuristic Scheduling Method for Automatic Manufacturing System
  • A Dynamic Weighted Heuristic Scheduling Method for Automatic Manufacturing System

Examples

Experimental program
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Embodiment

[0077] The dynamic weighted heuristic scheduling method of the automatic manufacturing system of the present invention includes the following contents:

[0078] 1. Use the Petri net to model an automatic manufacturing system, and obtain the Petri net model such as figure 2 shown.

[0079]2. Read the data values ​​corresponding to each library in the Petri net model established in the above 1, and further obtain the correlation matrix between the library places and transitions in the Petri net model according to the read data values.

[0080] The data value of the init file obtained in this example is:

[0081]

[0082] The association matrix of the matrix file in this embodiment is:

[0083]

[0084] 3. Based on the association matrix and heuristic A* search algorithm of the above 2, starting from the starting node S 0 Starting to expand the child nodes until all the target nodes are found, that is, the dynamic weighted heuristic search of the system is completed.

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Abstract

The invention discloses a dynamic weighted heuristic scheduling method of an automatic manufacturing system, which comprises the following steps: using Petri net to model the automatic manufacturing system; reading the data values ​​corresponding to each library in the Petri net model, and obtaining the Petri net The correlation matrix of places and transitions in the model; based on the correlation matrix and the heuristic A* search algorithm, it is possible to search and obtain the scheduling scheme of the system from the initial state node to the target node in a shorter time without predicting the depth of the scheduling scheme , and the quality of the scheduling scheme does not exceed the range given in advance. The invention takes the automatic manufacturing system as the object, adopts the dynamic weighting algorithm in the reachable graph, evaluates the nodes by adding additional weights to the heuristic function, and finds the path that best meets the requirements. This method sacrifices a small amount of scheduling result quality , can significantly speed up the speed of finding the optimal path, and effectively improve the efficiency in practical applications, and this method does not need to predict the depth of the system scheduling scheme in advance.

Description

technical field [0001] The invention relates to the field of automatic manufacturing systems, in particular to a dynamic weighted heuristic scheduling method for automatic manufacturing systems. Background technique [0002] Automated manufacturing systems are computer-controlled systems with limited resources that can handle different types of parts. In order to effectively operate an automated manufacturing system and make full use of system resources, it is necessary to coordinate and control the use of shared resources. Automated manufacturing systems include many types of systems, such as workshop manufacturing systems, flexible manufacturing systems, and the like. In an automated manufacturing system, available resources (e.g. machines, robots, drives, programs, etc.) can be shared among concurrently running processes (e.g. parts, vehicles, data, etc.), and they must compete for resource allocation and Achieve some system goals, such as maximizing makepan and minimiz...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B19/418
CPCG05B19/4185G05B2219/31088Y02P90/02
Inventor 黄波赵志霞戴晨谧蔡志成袁凤连
Owner NANJING UNIV OF SCI & TECH
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