摘要
冷链物流发展迅速,冷链物流需求预测的准确性对物流基础设施投入和物流政策制定是至关重要的。根据冷链物流需求受经济、社会发展和环境政策等不确定因素影响的特点,融合灰色理论与马尔科夫链,用灰色预测揭示系统时序变化的总体趋势,马尔科夫方法预测序列的随机波动的范围,能够优化灰色预测结果,提高预测的精度。将肉类、水产品、速冻面食、水果、蔬菜、奶类、药品等需要冷藏运输的产品产出总量作为冷链物流需求度量指标,建立灰色状态马尔科夫组合预测模型,对江苏省未来8年冷链物流需求量进行预测,预测结果可为江苏冷链物流发展战略制定、冷链物流服务体系构建和冷链物流园区建设等工作提供理论参考。
Cold,chain logistics has developed rapidly; the accuracy of the cold chain logistics is very important to the logistics infrastructure investment and logistics policy. According to the characteristic of logistics demand that is influenced by several uncertain factors, including the economy, social development, and environment policies, this paper integrates the Grey theory and Markov chain theory, uses Grey theory to reveal the general trend of system sequential change, and applies Markov method to predict the random fluctuation range of the sequential variation to be able to optimize prediction results and improve the accuracy of prediction. This paper takes the total yield of products that need refrigerated trans- port as the impact factors of transport aggregate of cold chain logistics, such as meat, aquatic products, quick-frozen noodle, fruits, vegetables, dairy, and medicine, and the prediction of Gray theory and Markov method are established to predict the logistics demand of Jiangsu. and forecasting results can be applied to provide theoretical reference and data support for making logistics development strategy and building logistics service system and logistics construction.
出处
《物流科技》
2015年第6期21-25,共5页
Logistics Sci-Tech
基金
国家自然科学基金项目
项目编号:70962008
国家自然科学基金项目
项目编号:71263040
江苏省社会科学基金项目
项目编号:13EYB013
中国制造业发展研究院项目
项目编号:SK20130090-5
