Multi-task real-time scheduling optimization method and system for industrial control all-in-one machine

By dynamically obtaining task lists, introducing window scrolling mechanisms and real-time scheduling constraint analysis in the industrial control all-in-one machine, and combining mixed optimization and optimization to find optimization, the problems of unreasonable task execution order and low resource utilization in traditional scheduling methods are solved, and efficient task scheduling and resource allocation are achieved.

CN119718591AInactive Publication Date: 2025-03-28SUZHOU DAN CRANE AUTOMATION TECH CO LTD
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Patent Information

Application Number
CN202510222506.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-27
Publication Date
2025-03-28
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The traditional task scheduling methods have problems in the industrial control all-in-one machine with unreasonable task execution order, delayed real-time task response and low resource utilization, which affects production efficiency and resource utilization.

Method used

By dynamically obtaining the task list of the target industrial control all-in-one machine, introducing a preset window scrolling mechanism for priority sorting, combining real-time scheduling constraints for analysis, and using the preset scheduling scheme fitness evaluation function in the hybrid optimization space for mixed optimization to obtain the optimal scheduling scheme.

Benefits of technology

It improves scheduling efficiency, optimizes resource allocation, ensures rapid response of real-time tasks, and improves the stability and efficiency of the production process.

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Abstract

The invention discloses a multi-task real-time scheduling optimization method and system for an industrial control all-in-one machine, and relates to the technical field of task scheduling, and the method comprises the steps: obtaining a target task list of a target industrial control all-in-one machine, and extracting a first task; introducing a preset window rolling mechanism to perform windowing priority ranking to obtain a target task sequence; receiving a real-time request task, obtaining a real-time scheduling constraint, analyzing a target task sequence, and determining a hybrid optimization space; obtaining an optimal sequence corresponding to the optimal scheduling scheme through hybrid optimization of a preset scheduling scheme fitness evaluation function in the hybrid optimization space; and replacing the target sequence with the optimal sequence to obtain a real-time task sequence of the target industrial control all-in-one machine. The technical problems of unreasonable task execution sequence, delayed real-time task response and low resource utilization in multi-task scheduling in the prior art are solved, and the technical effects of improving scheduling efficiency, optimizing resource allocation and ensuring quick response of real-time tasks are achieved.
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