Hybrid decision tree-based scheduling knowledge acquisition algorithm
Liu Wen-jian · Jisuanji yingyong yanjiu · 2007
A hybrid decision tree(DT)-based scheduling knowledge acquisition algorithm was presented.Genetic algorithm(GA) was combined with simulated annealing(SA) to develop a hybrid optimization method,in which SA was introduced to server as an adaptive mutation with changeable probability.The hybrid method was utilized to resolve the optimal attributes subset of manufacturing system and determine the optimal parameters of DT under different scheduling objectives;DT was used to evaluate the fitness of chromosome in the method and generate the scheduling knowledge after obtaining the optimal attri-butes subset and optimal DT's parameters.The experimental results demonstrate that the proposed algorithm produces significant performance improvements over other machine learning-based algorithms.