Multi-agent system task scheduling method and system for process industry
A multi-agent system and task scheduling technology, applied in manufacturing computing systems, data processing applications, instruments, etc., can solve problems such as low computing efficiency and falling into local optimum, and achieve the effect of poor solution results and excellent convergence speed
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Embodiment 1
[0040] The purpose of this embodiment is to provide a multi-agent system task scheduling method for the process industry.
[0041]Task scheduling in the manufacturing process refers to the planning, scheduling and arrangement of various production tasks in terms of space, time and resources under the condition of meeting the requirements of the process and existing production equipment; Multiple processes need to share resources and equipment, so production must be rationally planned through algorithms; the purpose of production task scheduling is to rationally plan and allocate resources, determine the processing time and sequence of products on different equipment, and improve production efficiency; process industry manufacturing process Task scheduling can be described as n jobs being processed on m machines; each job contains several production operations that must be performed on different machines. All jobs have the same processing order as they pass through the machine;...
Embodiment 2
[0093] The purpose of this embodiment is to provide a multi-agent system task scheduling system for the process industry.
[0094] A multi-agent system task scheduling system for the process industry, including:
[0095] Model building module, which is used to build an intelligent collaborative control model oriented to the whole process, which is composed of system Agents connected to Agents in each production stage through a bus;
[0096] A data acquisition module, which is used to acquire the required Agents for different tasks and the processing time data required by each Agent;
[0097] The optimal job sequence acquisition module is used to use the TS_QLearning algorithm to solve the optimal job sequence, and the intelligent collaborative control model performs task scheduling according to the job sequence.
Embodiment 3
[0099] The purpose of this embodiment is to provide an electronic device.
[0100] An electronic device, comprising, a memory, a processor, and a computer program stored on the memory, and the processor implements the following steps when executing the program, including:
[0101] Construct an intelligent collaborative control model oriented to the whole process, which is composed of system Agents connected to Agents in each production stage through the bus;
[0102] Obtain the initial job sequence of the task, as well as the on-site Agent required to complete each job and the processing time required to execute each on-site Agent described in each job;
[0103] Use the TS_QLearning algorithm to solve the job sequence with the shortest total idle time of the on-site Agent;
[0104] The intelligent collaborative control model performs task scheduling according to the job sequence.
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