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Optimal sales and operations planning for integrated steel industries

Author

Listed:
  • J. F. F. Almeida

    (Universidade Federal de Minas Gerais)

  • S. V. Conceição

    (Universidade Federal de Minas Gerais)

  • L. R. Pinto

    (Universidade Federal de Minas Gerais)

  • B. R. P. Oliveira

    (Instituto Federal de Minas Gerais)

  • L. F. Rodrigues

    (Universidade Federal de Minas Gerais)

Abstract

This paper aims at inspiring a change in the traditional approach of sales and operations planning (S&OP) of integrated steel industries that have reached a maturity planning level allowing the use of sophisticated technologies. Therefore, we propose a two-stage stochastic programming model suitable for reproducing the rolling horizon framework of tactical planning. Simulations of one year of operations in an integrated steel industry showed a potential improvement of about 15% on overall supply chain profit in comparison with a plan produced traditionally. Besides, we evaluated two scenarios to analyze the effects of a flexible plan when facing a tax raise and a capacity reduction. As a practical implication, the model provides a consensus view of the S&OP stages at once, supporting top managers to make better decisions. The two-stage modeling approach also reinforces the need for interaction of the sales team with procurement, production, and distribution teams.

Suggested Citation

  • J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.
    • Handle: RePEc:spr:annopr:v:315:y:2022:i:2:d:10.1007_s10479-020-03928-7
    DOI: 10.1007/s10479-020-03928-7
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    References listed on IDEAS

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    1. Fengqi You & Ignacio Grossmann, 2013. "Multicut Benders decomposition algorithm for process supply chain planning under uncertainty," Annals of Operations Research, Springer, vol. 210(1), pages 191-211, November.
    2. Tuomikangas, Nina & Kaipia, Riikka, 2014. "A coordination framework for sales and operations planning (S&OP): Synthesis from the literature," International Journal of Production Economics, Elsevier, vol. 154(C), pages 243-262.
    3. João Flávio de Freitas Almeida & Samuel Vieira Conceição & Luiz Ricardo Pinto & Ricardo Saraiva de Camargo & Gilberto de Miranda Júnior, 2018. "Flexibility evaluation of multiechelon supply chains," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-27, March.
    4. Houssem Felfel & Wafa Ben Yahia & Omar Ayadi & Faouzi Masmoudi, 2018. "Stochastic multi-site supply chain planning in textile and apparel industry under demand and price uncertainties with risk aversion," Annals of Operations Research, Springer, vol. 271(2), pages 551-574, December.
    5. Gabriel R. Bitran & Horacio H. Yanasse, 1982. "Computational Complexity of the Capacitated Lot Size Problem," Management Science, INFORMS, vol. 28(10), pages 1174-1186, October.
    6. Site Wang & Harsha Gangammanavar & Sandra Ekşioğlu & Scott J. Mason, 2020. "Statistical estimation of operating reserve requirements using rolling horizon stochastic optimization," Annals of Operations Research, Springer, vol. 292(1), pages 371-397, September.
    7. Goutam Dutta & Robert Fourer, 2001. "A Survey of Mathematical Programming Applications in Integrated Steel Plants," Manufacturing & Service Operations Management, INFORMS, vol. 3(4), pages 387-400.
    8. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    9. Buxey, Geoff, 2003. "Strategy not tactics drives aggregate planning," International Journal of Production Economics, Elsevier, vol. 85(3), pages 331-346, September.
    10. Céline Gicquel & Jianqiang Cheng, 2018. "A joint chance-constrained programming approach for the single-item capacitated lot-sizing problem with stochastic demand," Annals of Operations Research, Springer, vol. 264(1), pages 123-155, May.
    11. Ushnik Mukherjee & Azadeh Maroufmashat & Apurva Narayan & Ali Elkamel & Michael Fowler, 2017. "A Stochastic Programming Approach for the Planning and Operation of a Power to Gas Energy Hub with Multiple Energy Recovery Pathways," Energies, MDPI, vol. 10(7), pages 1-27, June.
    12. Agus Darmawan & Hartanto Wong & Anders Thorstenson, 2018. "Integration of promotion and production decisions in sales and operations planning," International Journal of Production Research, Taylor & Francis Journals, vol. 56(12), pages 4186-4206, June.
    13. Pedroso, Carolina Belotti & da Silva, Andrea Lago & Tate, Wendy Lea, 2016. "Sales and Operations Planning (S&OP): Insights from a multi-case study of Brazilian Organizations," International Journal of Production Economics, Elsevier, vol. 182(C), pages 213-229.
    14. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "Tactical supply chain planning models with inherent flexibility: definition and review," Annals of Operations Research, Springer, vol. 244(2), pages 407-427, September.
    15. Gopal P. Sinha & B. S. Chandrasekaran & Niloy Mitter & Goutam Dutta & Sudhir B. Singh & Aditya Roy Choudhury & P. N. Roy, 1995. "Strategic and Operational Management with Optimization at Tata Steel," Interfaces, INFORMS, vol. 25(1), pages 6-19, February.
    16. Houssem Felfel & Omar Ayadi & Faouzi Masmoudi, 2018. "Multi-stage stochastic supply chain planning in textile and apparel industry under demand uncertainty with risk considerations," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 29(3), pages 289-311.
    17. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "A tactical supply chain planning model with multiple flexibility options: an empirical evaluation," Annals of Operations Research, Springer, vol. 244(2), pages 429-454, September.
    18. Laura Laguna-Salvadó & Matthieu Lauras & Uche Okongwu & Tina Comes, 2019. "A multicriteria Master Planning DSS for a sustainable humanitarian supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 1303-1343, December.
    19. Pamela Danese & Margherita Molinaro & Pietro Romano, 2018. "Managing evolutionary paths in Sales and Operations Planning: key dimensions and sequences of implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(5), pages 2036-2053, March.
    20. Tibor Fabian, 1958. "A Linear Programming Model of Integrated Iron and Steel Production," Management Science, INFORMS, vol. 4(4), pages 415-449, July.
    21. Weskamp, Christoph & Koberstein, Achim & Schwartz, Frank & Suhl, Leena & Voß, Stefan, 2019. "A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand," Omega, Elsevier, vol. 83(C), pages 123-138.
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