摘要
从传统的本量利分析出发,首先针对运输服务企业的特点,建立运输服务企业的本量利和保本距离分析模型,结合铁路货物运输特殊性,搭建考虑运输作业效率和约束边界的保本距离分析模型,然后利用多相粒子群优化算法对模型进行求解分析,最后得到运价号对应的最小、最大保本距离。算例证明模型与算法有效且可行。结果表明:静载重、机车平均牵引重量和旅行速度变大而其他作业参数变小,运输成本降低,保本距离变小;运价号2和运价号3对应货物运输存在大于零的最小保本距离;大于最小保本距离的货物运输,可以通过调整作业参数实现盈利;各运价号对应货物运输最大保本距离大于1万km,即在实际情况下均不存在绝对盈利的运输距离。
Based on the analysis of traditional CVP model, targeting the characteristics of transportation service enterprises, this paper firstly proposed CVP model and break-even distance model for the transportation service enterprises. Combined with the particularity of railway freight transportation, the break-even distance model considering transport operation efficiency and constrained boundary was built next. Then the multi-phase parti- cle swarm optimization algorithm was used to analyze and solve the model. At last, the minimum/maximum break-even distance for each freight rate was obtained. The effectiveness and feasibility of the model and the al- gorithm were verified by a numerical example. The results showed that the transportation cost was lowered and the break-even distance was reduced with the increase of the static load, average load of locomotive and sched- ule speed, and decrease of the other operational parameters. Freight rate number 2 and number 3 corresponding to the freight transport showed, a minimum break-even distance, which is greater than zero. Freight transpor- tation distance that is greater than the minimum break-even distance can achieve profitability by adjusting the operation efficiency parameters. The maximum break-even distance for each freight rate is greater than 10,000 km. It means that there is no absolute profitable transportation distance for each freight rate in the actual ca- ses.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2016年第3期18-26,共9页
Journal of the China Railway Society
基金
中国铁路总公司科技研究开发计划(2014F008)
关键词
铁路运输
作业成本
多相粒子群优化
railway transportation
activity-based costing
multi-phase particle swarm optimization algorithm
