Management of the forestry production process taking into account external risks and existing experience from previous periods

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Abstract

A mathematical model for operational planning of a timber processing plant is presented. The problem of creating daily raw material supply chains from a commodity exchange and optimally utilizing production facilities is considered. Unlike existing approaches, the developed model allows for the consideration of raw material cutting technology and lot delivery times under uncertainty. Key output indicators are determined: the optimal profit trajectory over the planning horizon, daily production volumes, and raw material purchases. The model is tested using data from the Russian commodity exchange and a plant in Primorsky Krai. It is shown that even in complex scenarios, the model delivers significantly superior results and ensures stable planning. It is recommended for use to improve management efficiency at timber processing plants.

About the authors

Rodiоn S. Rogulin

Vladivostok State University

Author for correspondence.
Email: rafassiaofusa@mail.ru

Cand. Sci. (Economic), Associate Professor

Russian Federation, 41, Gogol St., 690014, Vladivostok

References

  1. Abdollah B., Ghasemi P., Chobar A. P., Sasouli M. R., Lajevardi M. A New Wooden Supply Chain Model for Inventory Management Considering Environmental Pollution: A Genetic algorithm. Foundations of Computing and Decision Sciences, 2022, no. 47, pp. 83–408. doi: 10.2478/fcds-2022-0021
  2. Salehi-Amiri A., Akbapour N., Hajiaghaei-Keshteli M., Gajpal Y., Jabbarzadeh A. Designing an effective two-stage, sustainable, and IoT based waste management system. Renewable and Sustainable Energy Reviews, 2022, no. 157(2), p. 112031. DOI: 112031.10.1016/j.rser.2021.112031
  3. Salehi-Amiri A., Zahedi A., Gholian-Jouybari F., Calvo E.Z.R., Hajiaghaei-Keshteli M. Designing a closed-loop supply chain network considering social factors; a case study on avocado industry. Applied Mathematical Modelling, 2022, no. 101, pp. 600–631. doi: 10.1016/j.apm.2021.08.035
  4. Daneshdoost F., Hajiaghaei-Keshteli M., Sahin R., Niroomand S. Tabu Search Based Hybrid Meta-Heuristic Approaches for Schedule-Based Production Cost Minimization Problem for the Case of Cable Manufacturing Systems. Informatica, 2022, no. 33(3), pp. 499–522. doi: 10.15388/21-INFOR471
  5. Chouhan V.K., Khan S.H., Hajiaghaei-Keshteli M. Sustainable planning and decision-making model for sugarcane mills considering environmental issues. J. of environmental management, 2022, no. 303(8), p. 114252. DOI: 114252.10.1016/j.jenvman.2021.114252
  6. Mondal A., Roy S.K. Multi-objective sustainable opened-and closed-loop supply chain under mixed uncertainty during COVID-19 pandemic situation. Computers & Industrial Engineering, 2021, no. 159(4), p. 107453. DOI: 107453.10.1016/j.cie.2021.107453
  7. Mondal A., Roy S.K., Midya S. Intuitionistic fuzzy sustainable multi-objective multi-item multi-choice step fixed-charge solid transportation problem. J. of Ambient Intelligence and Humanized Computing, 2021, no. 14(3), pp. 1–25. doi: 10.1007/s12652-021-03554-6
  8. Midya S., Kumar Roy S., Wilhelm Weber G. Fuzzy multiple objective fractional optimization in rough approximation and its aptness to the fixed-charge transportation problem. RAIRO-Operations Research, 2021, 55(3), pp. 1715–1741. doi: 10.1051/ro/2021078
  9. Taleizadeh A.A., Shahriari M., Sana S.S. Pricing and Coordination Strategies in a Dual Channel Supply Chain with Green Production under Cap and Trade Regulation. Sustainability, 2021, no. 13(21), article ID 12232. doi: 10.3390/su132112232
  10. Barman A., Das R., De P.K., Sana S.S. Optimal pricing and greening strategy in a competitive green supply chain: Impact of government subsidy and tax policy. Sustainability, 2021, no. 13(16), article ID 9178.
  11. Rana K., Singh S.R., Saxena N., Sana S.S. Growing items inventory model for carbon emission under the permissible delay in payment with partially backlogging. Green Finance, 2021, no. 3, pp. 153–174. doi: 10.3934/GF.2021009
  12. Sana S.S. A structural mathematical model on two echelon supply chain system. Annals of Operations Research, 2021, v. 315(2), pp. 1–29.
  13. Salehi-Amiri A., Zahedi A., Akbapour N., Hajiaghaei-Keshteli M. Designing a sustainable closed-loop supply chain network for walnut industry. Renewable and Sustainable Energy Reviews, 2021, v. 141, article ID 110821. doi: 10.1016/j.rser.2021.110821
  14. Chouhan V.K., Khan S.H., Hajiaghaei-Keshteli M. Metaheuristic approaches to design and address multi-echelon sugarcane closed-loop supply chain network. Soft Computing, 2021, no. 25, pp. 11377–11404. doi: 10.1007/s00500-021-05943-7
  15. Mosallanezhad B., Hajiaghaei-Keshteli M., Triki C. Shrimp closed-loop supply chain network design. Soft Computing, 2021, no. 11, pp. 7399–7422. doi: 10.1007/s00500-021-05698-1
  16. Hamdi-Asl A., Amoozad-Khalili H., Tavakkoli-Moghaddam R., Hajiaghaei-Keshteli M. Toward sustainability in designing agricultural supply chain network: A case study on palm date. Scientia Iranica, 2021. doi: 10.24200/sci.2021.58302.5659
  17. Fasihi M., Tavakkoli-Moghaddam R., Najafi S., Hajiaghaei M. Optimizing a bi-objective multi-period fish closed-loop supply chain network design by three multi-objective meta-heuristic algorithms. Scientia Iranica, 2021. doi: 10.24200/sci.2021.57930.5477
  18. Mosallanezhad B., Chouhan V.K., Paydar M.M., Hajiaghaei-Keshteli M. Disaster relief supply chain design for personal protection equipment during the COVID-19 pandemic. Applied Soft Computing, 2021, no. 112, p. 107809. DOI: 107809.10.1016/j.asoc.2021.107809
  19. Mousavi R., Salehi-Amiri A., Zahedi A., Hajiaghaei-Keshteli M. Designing a supply chain network for blood decomposition by utilizing social and environmental factor. Computers & Industrial Engineering. 2021, v. 160(1), p. 107501. DOI: 107501.10.1016/j.cie.2021.107501
  20. Zahedi A., Salehi-Amiri A., Hajiaghaei-Keshteli M., Diabat A. Designing a closed-loop supply chain network considering multi-task sales agencies and multi-mode transportation. Soft Computing, 2021, no. 8, pp. 6203–6235. doi: 10.1007/s00500-021-05607-6
  21. Rogulin R.S. Matematicheskaya model’ formirovaniya tsepochek postavok syr’ya s tovarno-syr’evoy birzhi v usloviyakh neopredelennosti [Mathematical Model of Formation of Raw Material Supply Chains from a Commodity Exchange under Uncertainty]. Biznes-informatika [Business Informatics], 2023, v. 17, no. 4. pp. 41–56. doi: 10.17323/2587-814X.2023.4.41.5
  22. Rogulin R.S. Model’ formirovanii lesopromyshlennykh tsepochek postavok syr’ya na sklad s uchetom osobennostey [Model of Formation of Forest Industry Raw Material Supply Chains to a Warehouse Taking into Account Specific Features]. Informatsionnye tekhnologii i vychislitel’nye sistemy [Information Technology and Computing Systems], 2023, no. 4, pp. 121–132.
  23. Pratiwi S.J. Pemanfaatan scm pengolahan bahan baku produksi kayu di cv. Interdisiplin Journal Social Science, 2025, no. 1(1), pp. 25–32.
  24. Al Kiramy R., Sari N., Putra Dieta D.W.D., Soleha A. Sosial media sebagai manajemen berbagi pengetahuan dalam rantai pasok. RJOCS, 2024, v. 10, no. 1, pp. 7–13.
  25. Bekele A.A., Mahesh G., Ingle P.V. Enhancing SMCs’ competitiveness through improving material supply chain management practice. International J. of Construction Management, 2024, no. 25(1), pp. 77–88.
  26. Gomaa A.H. Boosting Supply Chain Effectiveness with Lean Six Sigma. American J. of Management Science and Engineering, 2024, no. 9(6), pp. 156–171.
  27. Zhao J., Ji M., Feng B. Smarter supply chain: a literature review and practices. J. of Data, Information and Management, 2020, no. 2(2), pp. 95–110.
  28. Zekhnini K., Cherrafi A., Bouhaddou I., Benghabrit Y. Garza-Reyes J. A. Supply chain management 4.0: a literature review and research framework. Benchmarking: An International J., 2021, no. 28(2), pp. 465–501.
  29. Yazdi A.K., Hanne T., Osorio Gómez J.C. A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry. The TQM J., 2021, no. 33(8), pp. 1825–1844.
  30. Yang S. Analysis for supply chain management: evidence from Toyota. BCP Business & Management, 2022, no. 34, pp. 1204–1209.
  31. Yang M., Movahedipour M., Zeng J., Xiaoguang Z., Wang L. Analysis of Success Factors to Implement Sustainable Supply Chain Management Using Interpretive Structural Modeling Technique: A Real Case Perspective. Hindawi. Mathematical Problems in Engineering, 2017, no. 2017, pp. 1–14.
  32. Trubetskaya A., McDermott O., Brophy P. Implementing a customised Lean Six Sigma methodology at a compound animal feed manufacturer in Ireland. International J. of Lean Six Sigma, 2023, no. 14(5), pp. 1075–1095.

Supplementary files

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2. Fig. 1. The dependence of the stock of blanks of type l = 1 on time

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3. Fig. 2. Visualization of the trajectory of stocks of raw materials of type l = 2 in a warehouse

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4. Fig. 3. Visualization of the volume of production of goods of type k = 1

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5. Fig. 4. Visualization of the volume of production of goods of type k = 2

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6. Fig. 5. Visualization of production volumes of goods of type k = 3

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7. Fig. 6. Visualization of production volumes of goods of type k = 4

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8. Fig. 7. The average values of the optimal and received profit

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Copyright (c) 2025 Rogulin R.S.

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