COMBINATION PREDICTION METHOD FOR PORT LOGISTICS DEMAND BASED ON GENETIC ALGORITHM
Port logistics is an important component of the modem Logistics system, and the Logistics demand prediction is an important fundamental work for the port logistics system planning. This paper analyzes the limitationsof current different prediction methods for demand of port logistics, based on this, a grey-neural network predictioncombination method based on genetic algorithm is introduced. With improved genetic algorithm, this paper discusses and resolves the several problems related to the weight optimization of the grey neural network combinationprediction method, such as coding, fitness function, selection of genetic operator, ending condition of algorithm andtest of effectiveness. First, finds the results of the grey prediction method and the neural network prediction methodseparately, and then, calculates the weights and prediction values of combination model based on genetic algorithm.According to the comparative analysis between the actual value and the predicted value in Dalian port for past 10years, this combination prediction method is proved to be more effective, and it has higher accuracy than a singlemethod such as grey or neural network method.
Port logistics Combination model System Genetic algorithm Prediction
Mo Baomin Sun Guangqi Han Dechao
School of Transportation and Logistics Engineering,Dalian Maritime University,Dalian 116031,China
国际会议
第六届物流技术与装备国际学术会议(The 6th International Conference on Material Handling)(ICMH 2008)
北京
英文
112-115
2008-10-27（万方平台首次上网日期，不代表论文的发表时间）