Adapting the milp model to a complex mining system

Authors: LatyshevR. N.

Аssuming that local planning usually leads to sub-optimal solutions, this work aims to solve an integrated production, storage and distribution problem as part of a global supply chain system. The problem we address combines a lot sizing and distribution problem in a multilevel, multi-product, multi-period production network. To solve it, we propose a MILP (Mix Integer Linear Program) taking into consideration the local constraints of the different subsystems, but also the global ones that express the interactions between subsystems. This model proposes simultaneously a production, storage and transport plan that satisfies a known demand while minimizing total production, storage and distribution costs. Finally, the solutions found within this approach have the advantage of considering the system’s overall decisional cohesion as well as the constraints propagation in the various links of the chain. The originality of the work comes from the fact that we have addressed a multi-level lot-sizing problem, combined with a single rail transport problem. This integrated problem, to the best of our knowledge, has not been previously addressed. The model has been tested and tested on a real example of the mining industry, a comprehensive solution has been proposed for simultaneously planning the production, storage and distribution of resources in the mining industry.

Keywords: intergated lot sizing, transportation, linear optimization, mining industry, planning of production.
For citation:

Latyshev R. N. Adapting the milp model to a complex mining system. MIAB. Mining Inf. Anal. Bull. 2024;(11-1):143—156. [In Russ]. DOI: 10.25018/0236_1493_2024_111_0_143.

Acknowledgements:
Issue number: 11
Year: 2024
Page number: 143-156
ISBN: 0236-1493
UDK: 62.512
DOI: 10.25018/0236_1493_2024_111_0_143
Article receipt date: 01.07.2024
Date of review receipt: 05.10.2024
Date of the editorial board′s decision on the article′s publishing: 10.10.2024
About authors:

Latyshev R. N., assistant, junior research associate of the Department of Electrical Engineering Complexes, Novosibirsk State Technical University, Novosibirsk, Russia, 630073, e-mail: latyshev@corp.nstu.ru, ORCID ID: 0000-0002-3920-8728.

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Bibliography:

1. Kupriyanov V. V., Bondarenko I. S. Ensuring the Safety of Railway Transportation of Industrial Cargo at Mining Enterprises. Labor Safety in Industry. 2021, no. 4, pp. 56–62. [In Russ]. DOI: 10.24000/0409−2961−2021−4-56−62.

2. Razdymakha P. M., Shaferov V. I., Kuydin A. V. Trends in the modern development of the mining industry of Russia. Aktual’nyye voprosy kasayutsya razvitiya sovremennogo obshchestva i ekonomiki. 2023, no. 2, pp. 271–273. [In Russ].

3. Komilov T. O., Yakibov G. G. Improving the efficiency of operational indicators of railway transport. 2022, no. 2 (9), pp. 8–15. [In Russ]. DOI: https://doi.org/10.5281/ zenodo.5584563.

4. Isakhodjaev Kh. S., Norbutaev U. M., Azizova G. S., & Rasuleva N. M. Experimental study of an evaporative air cooler made of polymer fibers. Executive Editor, 50.5. Balovtsev

S. V., Merkulova A. M. Comprehensive assessment of the reliability of buildings, structures and technical devices of mining enterprises (2022). [In Russ].

5. Shishkin P. V., Efremenkov E. A., Qi M. Development of a Mathematical Model of Operation Reliability of Mine Hoisting Plants. Mathematics. 2024, 12, 1843. DOI: 10.3390/ math12121843.

6. Zakharova E. D. The use of innovative technologies in excursory activities on the example of St. Petersburg. Vestnik molodykh uchenykh Sankt-Peterburgskogo gosudarstvennogo universiteta tekhnologii i dizayna. — 2016. — No 2. — Pp. 305–310. [In Russ].

7. Kawalec W., Król R., Suchorab N. Regenerative Belt Conveyor versus Haul TruckBased Transport: Polish Open-Pit Mines Facing Sustainable Development Challenges. Sustainability. 2020, no. 12, p. 9215. DOI: https://doi.org/10.3390/su12219215.

8. Wheatley Greg, Rubel Robiul Islam. Analysis of conveyor drive power requirements in the mining industry. Acta Logistica. 2021, no. 8 (1), pp. 37–43. DOI: https://doi. org/10.22306/al.v8i1.200.

9. Zhironkin S., Szurgacz D. Mining Technologies Innovative Development: Economic and Sustainable Outlook. Energies. 2021, vol. 14, p. 8590. DOI: https://doi.org/10.3390/ en14248590.

10. Diaz K., Kammoun M. A., Hajej Z., Sefiani N., & Milazzo M. F. Joint production, transportation, and maintenance in downstream fuel supply chain. Proceedings of the Institution of Mechanical Engineers. Part O. Journal of Risk and Reliability. 2024. DOI: 10.1177/1748006X241229518.

11. Hilali H., Hovelaque V., & Giard V. Integrated planning and scheduling of a multi-site mining supply chain with blending, alternative routings and co-production. International Journal of Production Research. 2022, vol. 61(28), pp. 1–20. DOI: 10.1080/00207543.2022.2049909.

12. Kalauz K., Frits M., & Bertok B. Algorithmic model generation for multi-site multiperiod planning of clean processes by P-graphs. Journal of Cleaner Production. 2024, vol. 434, 140192. DOI: 10.1016/j.jclepro.2023.140192.

13. Karimi-Zare A., Shakouri G. H., Kazemi A., & Kim E.-S. Aggregate production planning and energy supply management in steel industry with an onsite energy generation system: A multi-objective robust optimization model. International Journal of Production Economics. 2024, vol. 269, 109149. DOI: 10.1016/j.ijpe.2024.109149.

14. Li M., Ming P., Huo R., Mu H., & Zhang C. Optimizing design and performance assessment of a sustainability hydrogen supply chain network: A multi-period model for China. Sustainable Cities and Society. 2023, vol. 92, 104444. DOI: 10.1016/j.scs.2023.104444.

15. Pérez-Perales D., Boza A., Alarcón F., & Gómez-Gasquet P. Mathematical programming-based methodology for the evaluation of supply chain collaborative planning scenarios. Annals of Operations Research. 2024, vol. 337, pp. 261–312. DOI: 10.1007/ s10479−024−05917−6.

16. Rakiz A., Absi N., & Fenies P. Comparing approaches for a multi-level planning problem in a mining industry. International Journal of Production Economics. 2023, vol. 265, 108999. DOI: 10.1016/j.ijpe.2023.108999.

17. Riera J. A., Lima R. M., & Knio O. M. A review of hydrogen production and supply chain modeling and optimization. International Journal of Hydrogen Energy. 2023, vol. 48(37), pp. 13731–13755. DOI: 10.1016/j.ijhydene.2022.12.242.

18. Wu L., Zhu Z., Feng Y., & Tan W. Economic analysis of hydrogen refueling station considering different operation modes. International Journal of Hydrogen Energy. 2024, vol. 52, pp. 1577–1591. DOI: 10.1016/j.ijhydene.2023.09.164.

19. Yusuf N., & Al-Ansari T. Current and future role of natural gas supply chains in the transition to a low-carbon hydrogen economy: A comprehensive review on integrated natural gas supply chain optimisation models. Energies. 2023, vol. 16(22), 7672. DOI: 10.3390/ en16227672.

20. Zaalouk A., Moon S., & Han S. Operations planning and scheduling in off-site construction supply chain management: Scope definition and future directions. Automation in Construction. 2023, vol. 153, 104952. DOI: 10.1016/j.autcon.2023.104952.

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