关键词: 动态调度, 特征选择, 二进制粒子群优化算法, 支持向量机

Abstract: A dynamic dispatching strategy selection approach for semiconductor production line was researched for quick and reasonable choice of scheduling strategies.Based on historical data,the Support Vector Machine(SVM)was selected as a data mining tool to obtain SVM-based dynamic scheduling strategy classification model with for production line by optimizing production attributes subset with Binary Particle Swarm Optimization(BPSO)algorithm.Under any given production status,an approximate optimal scheduling strategy could be acquired through this model in real-time.In the evaluation of scheduling strategies,a multi-object evaluation method based on power functions and entropy weight method was employed to extend the approach's application range.The effectiveness and feasibility of proposed dynamic scheduling approach was tested in an actual semiconductor production line.

Key words: dynamic scheduling, feature selection, binary particle swarm optimization algorithm, support vector machine