计算机工程与应用 ›› 2015, Vol. 51 ›› Issue (19): 24-27.

• 博士论坛 • 上一篇    下一篇

阔大货物装载加固方案多目标优化模型

谭政民1,彭其渊1,陈  思2,甘  蜜1   

  1. 1.西南交通大学 交通运输与物流学院,成都 610031
    2.西南交通大学峨眉校区,四川 峨眉 614202
  • 出版日期:2015-09-30 发布日期:2015-10-13

Multi-objective optimization model of loading reinforcement plan of railway long heavy goods

TAN Zhengmin1, PENG Qiyuan1, CHEN Si2, GAN Mi1   

  1. 1.College of Transportation & Logistics, Southwest Jiaotong University, Chengdu 610031, China
    2.Emei Campus, Southwest Jiaotong University, Emei, Sichuan 614202, China
  • Online:2015-09-30 Published:2015-10-13

摘要: 随着运输技术和需求的发展,阔大货物装载加固方案仅仅由承运单位和方案制定单位来确定已经不能满足铁路货物运输的发展,需要在确定货物装载加固方案时将客户需求考虑进去。基于层次分析法建立阔大货物装载加固方案多目标优化模型,首次将货主的客户需求纳入装载加固方案优化目标中,充分考虑方案制定者、方案使用者、客户3方面的需求。优化模型确定运输安全、运输时间、运输费用、客户满意度4个评价指标,给出4个一级目标的权重及运输安全的二级目标的权重。算例分析表明,对同一件阔大货物的3个装载加固方案进行多目标评价,针对不同的客户需求,可以得出较优方案。

关键词: 铁路运输, 阔大货物, 装载加固方案, 多目标优化, 层次分析法

Abstract: With development of transport technology and transportation demand, the loading reinforcement plan of railway long heavy goods is only decided by transportation enterprise and plan-making-company. It has been unable to meet the development of railway transport of goods. It needs consider the demand of customer at the same time. A multi-objective optimization model of the loading reinforcement plan is established by using Analytic Hierarchy Process(AHP). It is the first time that the customer demand is included in the loading plan optimization goals. It fully considers the demand of the plan-maker, the plan-user and customer. The four evaluation objectives are determined in the optimization model which is transportation security, transit time, transportation costs, and customersatisfaction. The weight of four first stage objective values and the second stage objective value safe of transport are confirmed. An application example shows that it can get a better plan by the comprehensive evaluation of three plans for different customer needs.

Key words: railway transportation, long heavy goods, loadingreinforcement plan, multi-objective optimization, Analytic Hierarchy Process(AHP)