Application of data mining algorithm in job shop scheduling problem
To extract dispatching rules from the ever-increasing workshop production data for guiding production scheduling tasks,a scheduling algorithm based on data mining was proposed.The minimize maximum completion time was set as the performance indicator,and a suitable scheduling sample set from the offline production data of the job shop was established.The established scheduling sample set was divided into training set and test set accord-ing to an appropriate ratio;then,the Classification and Regression Tree(CART)in the data mining algorithm was used to obtain effective scheduling knowledge from the training set,and a CART tree dispatching rule library was formed.To verify the effectiveness of the obtained dispatching rules,the obtained dispatching rules were combined with the genetic algorithm,and a genetic algorithm based on data mining and dispatching rules was designed as a scheduling algorithm to solve the job shop scheduling problem.Through the simulation and testing of different job shop classic examples,the effectiveness and superiority of the extracted dispatching rules and the scheduling algo-rithm were verified.
data miningjob shop schedulingclassification and regression treedispatching rules
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