Integrated scheduling of drayage and long-haul operations in synchromodal transport

被引:0
作者
Arturo E. Pérez Rivera
Martijn R. K. Mes
机构
[1] University of Twente,Department of Industrial Engineering and Business Information Systems
来源
Flexible Services and Manufacturing Journal | 2019年 / 31卷
关键词
Synchromodal transport; Drayage; Long-haul; Matheuristic; Approximate Dynamic Programming;
D O I
暂无
中图分类号
学科分类号
摘要
We study the problem of the integrated scheduling of drayage operations and long-haul transport in synchromodality. Although different in time span and characteristics of execution, these two processes have an impact on each other and their interaction has a direct influence on the overall performance of the transport network over time. We propose a simulation based integration of a Mixed-Integer Linear Programming model for the drayage operations and a Markov Decision Process model for the long-haul transport. We analyze the interfaces between these models, outline the challenges of integrating them, and design a heuristic approach to the simulation based integration. In a series of numerical experiments, we evaluate the cost savings compared to a non-integrated approach, using various transport network configurations. We show that our approach achieves average cost savings between 4 and 24% on networks with a majority of pre-haulage freights. Furthermore, we discuss limitations of our model and experiments, and provide guidelines for further research for the integrated scheduling of drayage and long-haul operations in synchromodal transport.
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页码:763 / 806
页数:43
相关论文
共 68 条
[1]  
Bai R(2014)Stochastic service network design with rerouting Transp Res Part B Methodol 60 50-65
[2]  
Wallace SW(2013)Integrated planning of loaded and empty container movements OR Spectr 35 457-478
[3]  
Li J(2009)A local search heuristic for the pre- and end-haulage of intermodal container terminals Comput Oper Res 36 2763-2772
[4]  
Chong AYL(2013)Decision support in intermodal transport: a new research agenda Comput Ind 64 105-112
[5]  
Braekers K(2009)Intelligent freight-transportation systems: assessment and the contribution of operations research Transp Res Part C Emerg Technol 17 541-557
[6]  
Caris A(2014)Scenario grouping in a progressive hedging-based meta-heuristic for stochastic network design Comput Oper Res 43 90-99
[7]  
Janssens G(2015)Modeling dry-port-based freight distribution planning Transp Res Part C Emerg Technol 55 518-534
[8]  
Caris A(2006)The single-node dynamic service scheduling and dispatching problem Eur J Oper Res 170 1-23
[9]  
Janssens G(2013)Dynamic approach to solve the daily drayage problem with transit time uncertainty Comput Ind 64 165-175
[10]  
Caris A(2007)Improved modeling and solution methods for the multi-resource routing problem Eur J Oper Res 180 1045-1059