Micro-electronics production line scheduling method based on index prediction and online learning

Abstract

The invention discloses a micro-electronics production line scheduling method based on index prediction and online learning, and belongs to the fields of advanced manufacturing, automation and information. The micro-electronics production line scheduling method based on the index prediction and the online learning is characterized by comprising the following steps: adopting an iterative decomposition algorithm based on a prediction mechanism, carrying out iterative decomposition on a to-be-solved micro-electronics production line scheduling problem into a scheduling sub problem of each stage and a remaining scheduling sub problem which is used for overall situation index prediction, adopting a self-adaption differential evolution method based on a resource conflict degree feature value to solve a multi-objective scheduling sub problem of a current stage, adopting a multi-fuzzy rule to solve the remaining scheduling sub problem of the current stage, and obtaining an overall situation index which corresponds to the remaining scheduling sub problem. Relevant data which are obtained in the solving process of scheduling sub problems of a plurality of stages are utilized, and a multi-fuzzy rule online learning framework is adopted to carry out online learning on the multi-fuzzy rule. The micro-electronics production line scheduling method based on the index prediction and the online learning is applied to a micro-electronics production line with a minimum average flow-through time and a maximum bottleneck machine utilization rate as scheduling targets, and good scheduling effect can be produced.

Description

technical field [0001] The invention belongs to the fields of advanced manufacturing, automation and information, and in particular relates to a scheduling method of a microelectronic production line with a reentrant feature. Background technique [0002] Aiming at the large-scale microelectronics production line scheduling problem with reentrant characteristics, there are currently several types of workpiece sequencing methods: model-based methods, intelligent optimization methods, and heuristic rule-based methods. Model-based sequencing methods need to attach some strong and unrealistic assumptions to the scheduling problem, so this type of method is mainly used to perform performance analysis on some typical and small-scale microelectronic production line scheduling problems; With a large scale, the method based on computational intelligence is also difficult to be directly applied; the sorting method based on heuristic rules is simple to implement, but this type of metho...

AI Technical Summary

Problems solved by technology

Model-based sequencing methods need to attach some strong and unrealistic assumptions to the scheduling problem, so this type of method is mainly used to perform performance analysis on some typical and small-scale microelectronic production line scheduling problems; With a large scale, the method based on computational intelligence is also difficult to be directly applied; the sorting method based on heuristic rules is simple to implement, but this type of method considers few factors, and it is generally difficult to obtain order for large-scale microelectronic production line scheduling problems. a satisfactory solution;

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