Job shop real-time scheduling method based on PCA-XGBoost-IRF

Abstract

The invention discloses a job shop real-time scheduling method based on PCA-XGBoost-IRF. The method comprises the steps of 1, constructing a standard data sample; 2, pre-processing the sample data, performing abnormal value processing, class imbalance processing and normalization processing on the sample data, and segmenting a data set to meet the input requirements for decision model construction; 3, carrying out feature engineering processing on a training set, wherein the feature engineering processing comprises feature extraction, feature importance calculation and feature selection; 4, carrying out decision model construction based on an improved random forest, including random forest model construction, improvement of an RF model to obtain an IRF model, and optimization of hyper-parameters of the IRF model based on grid search; 5, performing PCA-XGBoost-IRF decision model training based on the optimal parameters; and 6, realizing the real-time selection and decision-making of a dynamic job shop scheduling rule by using a decision-making model based on PCA-XGBoost-IRF. According to the present invention, the real-time scheduling method which is more reliable and higher in robustness and generalization is provided for the intelligent scheduling research based on data driving.

Description

technical field [0001] The invention relates to the technical field of machine learning and job shop scheduling, in particular to a PCA-XGBoost-IRF-based real-time job shop scheduling method. Background technique [0002] With the rapid development of artificial intelligence, industrial Internet, and computer information technology, a new wave of industrial revolution is sweeping under the background of intelligent manufacturing. Job-shop Scheduling Problem (JSP) is a typical NP-hard problem with strong engineering application background. As an interdisciplinary research field, since Johnson established the first mathematical model for scheduling two machines in 1954, it has received extensive attention from experts in multiple interdisciplinary fields such as computer and operations research. As the direct executor of manufacturing, the workshop carries a large number of production tasks and is also a meeting place for a large amount of real-time information. As the actua...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is: In order to overcome the problems of low practical operability, high calculation time cost and insufficient real-time response ability to workshop disturbances in the traditional job shop real-time scheduling method, the present invention provides a practically operable PCA-XGBoost-IRF-based real-time job shop scheduling method with high computational efficiency and real-time response to shop disturbances

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