多目标组合运输物流量预测建模算法

徐向阳; 王书翰; 汤鹏翔; 石刚

多目标组合运输物流量预测建模算法

北京航空航天大学汽车工程系, 北京 100083

详细信息

作者简介:
徐向阳(1965-),男,山东烟台人,教授,xxy@buaa.edu.cn.

中图分类号: U 491.14
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- 被引次数: 0
出版历程
- 收稿日期: 2006-05-15
- 网络出版日期: 2006-10-31

Algorithm of multi-objective prediction on logistics volume of combined transportation

Dept. of Automobile Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 提出了一种新的多目标组合运输物流量预测建模算法.以时间、领域、影响以及组合运输为基准,运用系统工程理论思想设计出一种四维的物流量影响因素模型,并运用结构方程模型对所建模型做了优化,提取出组合运输物流量的核心影响因素.在改进的神经网络算法的基础上结合遗传算法,提出了一种结合遗传算法的改进的神经网络新算法,弥补了改进的神经网络算法上的缺陷,在多目标组合运输物流量预测的实例应用中,该算法不仅有很高的预测精度,而且具有收敛速度快、运行稳定的特点.
- 多目标预测 /
- 组合运输物流量 /
- 结构方程模型 /
- 遗传算法 /
- 神经网络
Abstract: A new method was brought forward for the modeling of multi-objective prediction on logistics volume of combined transportation. Based on the standard of time, field, influence and combined transportation, using systems engineering antilogy, a model of four-dimensional factors of logistics volume was designedand optimized by using structural equation model. The fatal influencing factors of logistics volume of combined transportation were distilled. A new advanced neural network arithmetic integrated with genetic algorithm was put forward to make up the limitation of advanced neural network, and applied in a example of multi-objective prediction on logistics volume of combined transportation. Results show that this advanced algorithm performs steadily with high precision and convergence speed.
- multi-objective prediction /
- logistics volume of combined transportation /
- structural equation model /
- genetic algorithm /
- neural network

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参考文献(1)

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