A hybrid algorithm to solve the flexible oil refinery production planning problem

Document Type : Industry Article

Authors

Department of Industrial Engineering, Faculty of Engineering, Payame Noor University, Tehran, Iran

Abstract

The goal of production planning in a refinery is to produce as many valuable products as possible such as gasoline, jet fuel, diesel, etc., while meeting market demand and other constraints. Crude oil refining is one of the most complex chemical industries; Therefore, optimizing the production planning of an oil refinery is considered as one of the most difficult and challenging issues in this field. Due to rapid changes in industry-related technologies such as the construction of new catalysts, the design of more flexible process units, the flexibility of refineries is increasing rapidly. With the flexibility of refineries, their production planning requires a mathematical model that can be used to make the best decision at the right time to meet market demand at the lowest production cost. In this paper, the production planning of a flexible refinery is modeled using mathematical relationships between macro parameters such as product demand, production conditions, fixed and variable production costs, and inventory costs of petroleum products. To solve it, a hybrid algorithm of combining genetic algorithm and fix and optimize is proposed. The results with using of 63 simulated problems in small, medium and large dimensions show that the near-optimal solution obtained from the hybrid method deviates 0.23 and 0.12 percent of the exact solution of the problem on average in small and medium dimensions respectively. Also in large dimensions where it was not possible to calculate the exact answer by the computer, this algorithm can answer in an average of 87 seconds.

Keywords

Main Subjects


[1] H. Chen, “Fix-and-optimize and variable neighborhood search approaches for multi-level capacitated lot sizing problems”, Omega, Vol. 56, No.1, October 2015, pp. 25-36.
[2] I. E. Grossmann, S. A. Van Den Heever, and I. Harjunkoski, “Discrete optimization methods and their role in the integration of planning and scheduling”, In AIChE Symposium Series, New York; American Institute of Chemical Engineers, Vol. 1, No. 1, March 2002, pp. 150-168.
[3] K. Y. Al-Qahtani, and A. Elkamel, Planning and integration of refinery and petrochemical operations. John Wiley & Sons, 2011.
[4] J. G. Speight, The refinery of the future, Gulf Professional Publishing, 2020.
[5] J. G. Speight, An introduction to petroleum technology, economics, and politics, John Wiley & Sons, 2011.  
[6] R. Beck, A vision for the refinery of 2030, Hydrocarbon Process, 2019.
[7] Canadian Fuels Association, The Economics of Petroleum Refining-Understanding the business of processing crude oil into fuels and other value added products, December 2013.
[8] M. Joly, “Refinery production planning and scheduling: The refining core business”, Brazilian Journal of Chemical Engineering, Vol. 29, No. 2, June 2012, pp. 371-84.
[9] L. F. L. Moro, A. C. Zanin, and J. M. Pinto, “A planning model for refinery diesel production”, Computers & Chemical Engineering, Vol. 22, No. 1, March 1998, pp.S1039-S1042.
[10] W. Li, C.W. Hui, C. W., and A. Li, “Integrating CDU, FCC and product blending models into refinery planning”, Computers & chemical engineering, Vol. 29, No. 9, August 2005, pp. 2010-2028.
[11] I. Alhajri, A. Elkamel, T. Albahri, and P.L. Douglas, “A nonlinear programming model for refinery planning and optimisation with rigorous process models and product quality specifications” International Journal of Oil, Gas and Coal Technology, Vol. 1, No. 3, August 2008, pp. 283-307. 
[12] رضا درگاهی و محمدرضا جعفری نصر، " کاربرد مدل برنامه ریزی خطی در فرایند مخلوط سازی بنزین تولیدی پالایشگاه تهران"، پژوهش نفت، دوره 19، شماره 60، زمستان 1388، صفحه 67-83.
[13] A.M. Alattas, I.E. Grossmann, and I. Palou-Rivera, “Integration of nonlinear crude distillation unit models in refinery planning optimization”, Industrial & engineering chemistry research, Vol. 50, No. 11, April 2011, pp. 6860-6870.
[14] A.M. Alattas, I.E. Grossmann, I. Palou-Rivera, “Refinery production planning: multiperiod MINLP with nonlinear CDU model”, Industrial & engineering chemistry research, Vol. 51, No. 39, August 2012, pp.12852-12861.
[15] B.J. Zhang, K. Liu, X.L. Luo, Q.L. Chen, and W.K. Li, “A multi-period mathematical model for simultaneous optimization of materials and energy on the refining site scale”, Applied Energy, Vol. 143, No. 1, April 2015, pp.238-250.
[16] J. Li, X. Xiao, F. Boukouvala, C.A. Floudas, B. Zhao, G. Du, X. Su, and H. Liu, “Data‐driven mathematical modeling and global optimization framework for entire petrochemical planning operations”, AIChE Journal, Vol. 62, No. 9, March 2016, pp. 3020-3040.
[17] M.R. Siamizade, “Global optimization of refinery-wide production planning with highly nonlinear unit models”, Industrial & Engineering Chemistry Research, Vol. 58, No. 24, May 2019, pp. 10437-10454.
[18] F. Li, M. Yang, W. Du, and X. Dai, “Development and challenges of planning and scheduling for petroleum and petrochemical production”, Frontiers of Engineering Management, Vol. 7, No. 1, July 2020, pp. 373-383.
[19] L. Zhang, Z. Yuan, and B. Chen, “Refinery-wide planning operations under uncertainty via robust optimization approach coupled with global optimization”, Computers & Chemical Engineering, Vol. 146, No .1, March 2021, p.107205.
[20] مرتضی اصغری، شیرین قربان لوینه و مجتبی راجی، "شبیه‌سازی عددی و مطالعه نظری تأثیر پارامترهای عملیاتی در تقطیر غشایی در خلأ"، مدل‌سازی در مهندسی، دوره 16، شماره 55، زمستان 1397، صفحه 41-49.
[21] سید حسین ابراهیمی و احمد جعفرزاده افشاری، "ارایه یک مدل ریاضی جهت بهینه‏ سازی عملیات شبکه انتقال گاز"، مدل‌سازی در مهندسی، دوره 14، شماره 44، بهار 1395، صفحه 93-104.
[22] N.M. Noh, A. Bahar, and Z.M. Zainuddin, “Scenario Based Two-Stage Stochastic Programming Approach for the Midterm Production Planning of Oil Refinery”, MATEMATIKA: Malaysian Journal of Industrial and Applied Mathematics, Vol. 34, No. 3, December 2018, pp. 45-55.
[23] L.D. Sales, F.M. Luna, and B.D. Prata, “An integrated optimization and simulation model for refinery planning including external loads and product evaluation”, Brazilian Journal of Chemical Engineering, Vol. 35, No. 1, January 2018, pp. 199-215.
[24] J. Shin, and J.H. Lee, “Multi-timescale, multi-period decision-making model development by combining reinforcement learning and mathematical programming”, Computers & Chemical Engineering, Vol. 121, No. 1, February 2019, pp.556-573.
[25] F.A. Utomo, C.N. Rosyidi, and W.A. Jauhari, “An integrated optimisation model of refinery short-term planning: a case study”, Energy Systems, Vol. 11, No. 2, November 2020, pp. 283-299.
[26] C.D. Demirhan, F. Boukouvala, K. Kim, H. Song, W.W. Tso, C.A. Floudas, and E.N. Pistikopoulos, “An integrated data-driven modeling & global optimization approach for multi-period nonlinear production planning problems”, Computers & Chemical Engineering, Vol. 141, No. 1, October 2020, p.107007.
[27] F. Li, F. Qian, C. Fan, and V. Mahalec, “Hinging Hyperplanes Crude Oil Mixing Model for Production Planning Optimization”, Industrial & Engineering Chemistry Research, Vol. 59, No. 18, April 2020, pp. 8704-8714.
[28] C. Wang, X. Peng, C. Shang, C. Fan, L. Zhao, and W. Zhong, “A deep learning-based robust optimization approach for refinery planning under uncertainty”, Computers & Chemical Engineering, Vol. 155, No. 1, December 2021, p. 107495.
[29] J.M. Pinto, and L.F. Moro, “A planning model for petroleum refineries”, Brazilian Journal of Chemical Engineering, Vol. 17, No. 4-7, December 2000, pp.575-586.
[30] S.M. Neiro, and J.M. Pinto, “A general modeling framework for the operational planning of petroleum supply chains”, Computers & Chemical Engineering, Vol. 28, No. 6-7, June 2004, pp. 871-896.
[31] B.C. Menezes, L.F. Moro, I.E. Grossmann, J.D. Kelly, R.A. Medronho, and F.P. Pessoa, “Production planning of oil-refinery units for the future fuel market in Brazil”, COBEQ, Florianopolis, 19-22 October 2014.
[32] P. Castillo Castillo, P.M. Castro, and V. Mahalec, “Global optimization algorithm for large-scale refinery planning models with bilinear terms”, Industrial & Engineering Chemistry Research, Vol. 56, No. 2, December 2017, pp.530-548.
[33] A. Azadeh, F. Shafiee, R. Yazdanparast, J. Heydari, and A. Keshvarparast, “Optimum integrated design of crude oil supply chain by a unique mixed integer nonlinear programming model”, Industrial & Engineering Chemistry Research, Vol. 56, No. 19, April 2017, pp. 5734-5746.
[34] P. Tominac, and V. Mahalec, “A game theoretic framework for petroleum refinery strategic production planning”, AIChE Journal, Vol. 63, No. 7, July 2017, pp. 2751-2763.
[35] امیر رحیمی منش، حمزه امین طهماسبی و کامبیز  شاهرودی، "ارائه مدل بهینه‌سازی ریاضی برای زنجیره تأمین چند محصولی با امکان وقوع اختلال در تأمین‌کننده در شرایط تحریم (مطالعه موردی صنایع تعمیراتی پالایشگاهی)"، مدل‌سازی در مهندسی، دوره 18، شماره 60، بهار 1399، صفحه 107-125.
[36] C.S. Hsu, and P.R. Robinson, Handbook of Petroleum Technology, Springer International Publishing AG, Cham, 2017.
[37] T. Olsen, and E. Schodowski, “Improve refinery flexibility and responsiveness”, Hydrocarbon Processing,  Vol. 15, No. 1, January 2015, pp. 87-89.
[38] J.G. Speight, Handbook of industrial hydrocarbon processes, Gulf Professional Publishing, 2019.
[39] J.O. Cunha, H.H. Kramer, and R.A. Melo, “On the computational complexity of uncapacitated multi-plant lot-sizing problems”, Optimization Letters, Vol. 15, No. 2, July 2021, pp. 803-812.
[40] C. Devoto, E. Fernández, and P. Piñeyro, “The economic lot-sizing problem with remanufacturing and inspection for grading heterogeneous returns”, Journal of Remanufacturing, Vol. 11, No. 1, April 2021, pp. 71-87.
[41] V. Bo, M. Bortolini, E. Malaguti, M. Monaci, C. Mora, and P. Paronuzzi, “Models and algorithms for integrated production and distribution problems”, Computers & Industrial Engineering, Vol. 154, No. 1, April 2021, p. 107003.
[42] Set Laboratories Inc., Refining Operations. Retrieved from here: http://www.setlab.com/resources/refining/refining-operations , Jan. 05, 2022.
[43] S. Parkash, Refining processes handbook, Elsevier, 2003.
[44] J.H. Gary, J.H. Handwerk, M.J. Kaiser, and D. Geddes, Petroleum refining: technology and economics, CRC press, 2007.
[45] J.G. Speight, The Chemistry and Technology of Petroleum, CRC Press, 2006.
[46] J.G. Speight, Handbook of petroleum refining, CRC press, 2016.
 
[47] L. Dong, P. Kouvelis, and X. Wu, “The value of operational flexibility in the presence of input and output price uncertainties with oil refining applications”, Management Science, Vol. 60, No. 12, October 2014, pp. 2908-2926.
[48] مسعود رضائی، غلامرضا اسماعیلیان و رامین صادقیان، "الگوریتم دوبعدی ثابت سازی –بهینه‌سازی برای حل مسأله تعیین اندازه انباشته در سیستم‌های تولیدی انعطاف‌پذیر با محصولات همبسته"، مدیریت تولید و عملیات، دوره 12، شماره 2، تابستان 1400، صفحه 93-111.
[49] S. Helber, and F. Sahling, “A fix-and-optimize approach for the multi-level capacitated lot sizing problem”, International Journal of Production Economics, Vol. 123, No. 2, February 2010, pp. 247-256.
[50] S. K. Karna, and R. Sahai, “An overview on Taguchi method”, International journal of engineering and mathematical sciences, Vol. 1, No. 1, January 2012, pp. 1-7.
[51] U.S. Energy Information Administration, Available from: https://www.eia.gov/dnav/pet , Accessed Sep. 16, 2021.