| Summary: | 碩士 === 國立高雄第一科技大學 === 運輸倉儲營運所 === 91 === With the development of information technology, varieties of products and variation of customer demand make organization not have sufficient information to respond customer’s demand. Furthermore, uncertainty about short-run product demand also build up obstacles to forecast. Therefore, it is a hot issue to set up a model which can predict more accurate downward-stream demand.
A simulation model embedded five demand forecast models: Moving Average Forecasting Model, Time Series Forecasting Model, Constant-value Forecasting Model, Stage-Learning Genetic Algorithms Forecasting Model, Continue-Learning Genetic Algorithms Forecasting Model, is used to simulate and analyze the proposed VMI supply chain system. Among the five demand forecast models, the prediction error of Continue-Learning Genetic algorithms Forecasting Model is smallest. Therefore, variation of inventory level in Continue-Learning Genetic algorithms Forecasting Model is the most stable also.
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