Optimum Utilisation of Rolling Stocks for Iron Ore Mining Industries

Shi Qiang Liu; Erhan Kozan

doi:10.4028/www.scientific.net/AMR.361-363.1529

Paper Titles

Hybrid Strategy for Product Quality Credit Evaluation Based on Statistics and Artificial Neural Network
p.1499

Research on Diesel Engine Fault Diagnosis Modeling Based on Elman Neural Network
p.1506

Inter-Regional Power-Generation Economic Exchange Analysis Model under Environmental Constraints
p.1510

Reliability Evaluation of Planning Distribution Network
p.1524

Optimum Utilisation of Rolling Stocks for Iron Ore Mining Industries
p.1529

Sustainable Development Study of Resource-Based City from the Perspective of Circular Economy
p.1535

Accelerate the Rural Ecological Environment in Dalian Actively Promote the Development of Circular Economy
p.1539

Numerical Simulation of Temperature Field for Bedrock Fracture Groundwater at Zhangzhou Geothermal Field
p.1547

Finite Element Analysis of Moving Trestle of CNC Machine Tool
p.1553

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 361-363Optimum Utilisation of Rolling Stocks for Iron Ore...

Optimum Utilisation of Rolling Stocks for Iron Ore Mining Industries

Abstract:

In this paper, a generic and flexible optimisation methodology is developed to represent, model, solve and analyse the iron ore supply chain system by integrating of iron ore shipment, stockpiles and railing within a whole system. As a result, an integrated train-stockpile-ship timetable is created and optimised for improving efficiency of overall supply chain system. The proposed methodology provides better decision making on how to significantly improve rolling stock utilisation with the best cost-effectiveness ratio. Based on extensive computational experiments and analysis, insightful and quantitative advices are suggested for iron ore mine industry practitioners. The proposed methodology contributes to the sustainability of the environment by reducing pollution due to better utilisation of transportation resources and fuel.

You might also be interested in these eBooks

Natural Resources and Sustainable Development

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 361-363)

Pages:

1529-1534

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.361-363.1529

Citation:

Cite this paper

Online since:

October 2011

Authors:

Shi Qiang Liu, Erhan Kozan

Keywords:

Iron Ore, Mining, Resources Utilisation, Saving Energy, Scheduling

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] X. Zhou and M. Zhong. Bicriteria train scheduling for high-speed passenger railroad planning applications. European Journal of Operational Research, Vol. 167, 752–771, (2005).

DOI: 10.1016/j.ejor.2004.07.019

Google Scholar

[2] A. Caprara, M. Monaci, P. Toth and P.L. Guida. A Lagrangian heuristic algorithm for a real-world train timetabling problem. Discrete Applied Mathematics, Vol. 154, 738 –753, (2006).

DOI: 10.1016/j.dam.2005.05.026

Google Scholar

[3] M. Carey and I. Crawford. Scheduling trains on a network of busy complex stations. Transportation Research Part B, Vol.41, 159-178, (2007).

DOI: 10.1016/j.trb.2006.02.002

Google Scholar

[4] V. Cacchiani, A. Caprara and P. Toth. A column generation approach to train timetabling on a corridor. A Quarterly Journal of Operations Research, Vol.6, 125-142, (2008).

DOI: 10.1007/s10288-007-0037-5

Google Scholar

[5] F. Corman, A. D'Ariano, D. Pacciarelli and M. Pranzo. A tabu search algorithm for rerouting trains during rail operations. Transportation Research Part B, Vol.44, 175–192, (2010).

DOI: 10.1016/j.trb.2009.05.004

Google Scholar

[6] J.T. Krasemann. Design of an effective algorithm for fast response to the re-scheduling of railway traffic during disturbances. Transportation Research Part C, doi:10.1016/j.trc. 2010.12.004, (2011).

DOI: 10.1016/j.trc.2010.12.004

Google Scholar

[7] R.L. Burdett and E. Kozan. Techniques for inserting additional trains into existing timetables. Transportation Research Part B, Vol.43, 821-836, (2009).

DOI: 10.1016/j.trb.2009.02.005

Google Scholar

[8] R.L. Burdett and E. Kozan. Development of a disjunctive graph model and constructive algorithms for train scheduling. European Journal of Operational Research, Vol.200(1), 85-98, (2010).

DOI: 10.1016/j.ejor.2008.12.005

Google Scholar

[9] S.Q. Liu, and E. Kozan. Scheduling trains as a blocking parallel-machine job shop scheduling problem. Computers and Operations Research, Vol.36, 2840-2852, (2009).

DOI: 10.1016/j.cor.2008.12.012

Google Scholar

[10] S.Q. Liu, and E. Kozan. A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem. Journal of the Operational Research Society, doi:10.1057/jors.2011.4, (2011).

DOI: 10.1057/jors.2011.4

Google Scholar

[11] S.Q. Liu, and E. Kozan. Scheduling trains with priorities: a no-wait blocking parallel-machine job-shop scheduling model. Transportation Science, doi: 10.1287/trsc.1100.0332, (2010).

DOI: 10.1287/trsc.1100.0332

Google Scholar