A Discrete Manufacturing Workshop Scheduling Method Based on Improved Multi-objective Jaya Algorithm

Abstract

The present invention provides a production scheduling method for discrete manufacturing workshops based on the improved multi-objective Jaya algorithm, which has high accuracy, effectively improves the rationality and production efficiency of production plan layout, and has good energy saving and emission reduction effects. It includes the following steps , through the Internet of Things system to monitor the real-time status of discrete manufacturing workshops, and through data processing, analyze and judge the impact of abnormal conditions on the processing time of workpieces. If abnormal conditions affect the processing time of workpieces, the information of abnormal conditions will also be input to In the production scheduling system, through the evaluation system of the production scheduling system, the maximum completion time and the carbon emission of the workshop are at the minimum level at the same time, and the mathematical optimization model and the improved multi-objective Jaya algorithm for statistical optimization are mainly based on machine tools. Obtain the optimal production scheduling plan.

Description

technical field [0001] The invention relates to the technical field of intelligent manufacturing, in particular to a production scheduling method for a discrete manufacturing workshop based on an improved multi-objective Jaya algorithm. Background technique [0002] The machinery manufacturing industry provides technical equipment for the entire national economy, but at the same time it consumes a lot of resources and energy and generates carbon emissions in the production process, which has an impact on the environment. For example, carbon emissions will not only affect climate change, but also acidify the ocean and soil imbalance. Therefore, a reasonable production plan plays an important role in controlling energy consumption in production and processing, reducing carbon emissions, and realizing a green, low-carbon, and sustainable production model. [0003] In discrete manufacturing workshops, the main factors affecting energy consumption and carbon emissions include mac...

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Problems solved by technology

[0005] Aiming at the shortcomings of the existing discrete manufacturing workshop production planning and scheduling methods with low accuracy, unreasonable production scheduling scheme, poor energy saving and emission reduction effect, and low production efficiency, the present invention provides a discrete manufacturing based on the improved multi-objective Jaya algorithm. The production scheduling method in the workshop has high accuracy, effectively improves the rationality of production planning and production efficiency, and has a good effect on energy saving and emission reduction

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