Experimental dataset for optimising the freight rail operations

Data in Brief

Shi Qiang Liu¹  Mahmoud Masoud²  Erhan Kozan²  Geoff Kent² 

[1] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu City 6117563, Sichuan Province, China;Science and Engineering Faculty, Queensland University of Technology, 2 George St, GPO Box 2434, Brisbane, QLD 4001, Australia;

关键词: Fright Rail Systems;    Train Scheduling;    Metaheuristic;    Constraint Programming;   

DOI  :  10.1016/j.dib.2016.09.015

来源: DOAJ

【 摘 要 】

The freight rail systems have an essential role to play in transporting the commodities between the delivery and collection points at different locations such as farms, factories and mills. The fright transport system uses a daily schedule of train runs to meet the needs of both the harvesters and the mills (An Integrated Approach to Optimise Cane Rail Operations (M. Masoud, E. Kozan, G. Kent, Liu, Shi Qiang, 2016b) [1]). Producing an efficient daily schedule to optimise the rail operations requires integration of the main elements of harvesting, transporting and milling in the value chain of the Australian agriculture industry. The data utilised in this research involve four main tables: sidings, harvesters, sectional rail network and trains. The utilised data were collected from Australian sugar mills as a real application. Operations Research techniques such as metaheuristic and constraint programming are used to produce the optimised solutions in an analytical way.

【 授权许可】

Unknown