zbMATH — the first resource for mathematics

Petroleum refinery optimization. (English) Zbl 1390.90623
Summary: In the face of lower margins, stiffer competition, and ever more stringent product and environmental specifications, petroleum refineries have increasingly relied on optimization approaches to maintain their survival and competitive edge. In this paper, we present a comprehensive overview of the current state of the art role of optimization methods in refineries for wide-ranging multiscale applications and activities spanning the traditional planning linear programming to supply chain that extends to outside-the-fence considerations. The paper aims to provide an integrated treatment of techniques and tools, and a survey of representative work in the burgeoning literature of this field with an emphasis on comparisons between industrial practices and academic research.

90C90 Applications of mathematical programming
90B90 Case-oriented studies in operations research
90B30 Production models
90B06 Transportation, logistics and supply chain management
Full Text: DOI
[1] Adams J, Biroli S (2002) Benefits of the FCC RTO to AgipPetroli. Paper presented at the Aspenworld conference 2002
[2] Adhitya, A; Srinivasan, R; Karimi, IA, Heuristic rescheduling of crude oil operations to manage abnormal supply chain events, AIChE J, 53, 397-422, (2007)
[3] Adhitya, A; Srinivasan, R; Karimi, IA, A model-based rescheduling framework for managing abnormal supply chain events, Comput Chem Eng, 31, 496-518, (2007)
[4] Adhya, N; Tawarmalani, M; Sahinidis, NV, A Lagrangian approach to the pooling problem, Ind Eng Chem Res, 38, 1956-1972, (1999)
[5] Akrotirianakis, IG; Floudas, CA, Computational experience with a new class of convex underestimators: box-constrained NLP problems, J Glob Optim, 29, 249-264, (2004) · Zbl 1133.90420
[6] Akrotirianakis, IG; Floudas, CA, A new class of improved convex underestimators for twice continuously differentiable constrained nlps, J Glob Optim, 30, 367-390, (2005) · Zbl 1082.90090
[7] Alattas, AM; Grossmann, IE; Palou-Rivera, I, Integration of nonlinear crude distillation unit models in refinery planning optimization, Ind Eng Chem Res, 50, 6860-6870, (2011)
[8] Alattas, AM; Grossmann, IE; Palou-Rivera, I, Refinery production planning: multiperiod MINLP with nonlinear CDU model, Ind Eng Chem Res, 51, 12852-12861, (2012)
[9] AllBusiness (2013) Invensys and ChevronTexaco sign marketing agreement for PETRO refinery planning system. http://www.allbusiness.com/company-activities-management/management-benchmarking/5921349-1.html. Accessed 12 July 2013
[10] Al-Qahtani, K; Elkamel, A, Robust planning of multisite refinery networks: optimization under uncertainty, Comput Chem Eng, 34, 985-995, (2010)
[11] Aspen Technology (2005) aspenONE planning, scheduling and blending for petroleum. http://www.aspentech.com/brochures/psb%20brochure.pdf
[12] Aspen Technology (2011a) Aspen Custom Modeler\^{}{®}. http://www.aspentech.com/products/aspen-custom-modeler.aspx · Zbl 1180.90250
[13] Aspen Technology I (2011b) Aspen InfoPlus.21\^{}{®} family. https://www.aspentech.com/products/aspen-infoplus21/
[14] Aspen Technology I (2011c) Aspen PIMS™ family 4.0: advanced planning, scheduling, and blending. http://www.aspentech.com/brochures/aspen_pims_family.pdf
[15] Aspen Technology I (2012a) Aspen FCC: a simulation system for monitoring, planning and optimizing fluid catalytic cracking units. http://www.aspentech.com/brochures/fcc.pdf. Accessed 15 Apr 2013
[16] Aspen Technology I (2012b) Aspen refinery multi-blend optimizer. http://www.aspentech.com/products/aspen-mbo.cfm. Accessed 18 May 2012
[17] Aspen Technology I (2013a) Aspen DMCplus-AspenTech. http://www.aspentech.com/products/aspen-dmcplus/. Accessed 8 Aug 2013 · Zbl 0791.90056
[18] Aspen Technology I (2013b) Aspen fleet optimizer. http://www.aspentech.com/core/aspen-retail.aspx. Accessed 10 May 2013
[19] Aspen Technology I (2013c) Aspen petroleum scheduler. http://www.aspentech.com/products/aspen-orion-xt.cfm. Accessed 10 May 2013
[20] Aspen Technology I (2013d) Aspen petroleum supply chain planner. http://www.aspentech.com/products/aspen-distribution-planning-optimization.aspx. Accessed 24 Apr 2013
[21] Aspen Technology I (2013e) Aspen PIMS and Aspen PIMS-AO. http://www.aspentech.com/brochures/aspen_pims_ao.pdf. Accessed 15 Aug 2013
[22] Barbaro, A; Bagajewicz, MJ, Managing financial risk in planning under uncertainty, AIChE J, 50, 963-989, (2004)
[23] Belotti, P; Kirches, C; Leyffer, S; Linderoth, J; Luedtke, J; Mahajan, A, Mixed-integer nonlinear optimization, Acta Numer, 22, 1-131, (2013) · Zbl 1291.65172
[24] Benders, JF, Partitioning procedures for solving mixed-variables programming problems, Numer Math, 4, 238-252, (1962) · Zbl 0109.38302
[25] Bodington, CE; Baker, TE, A history of mathematical-programming in the petroleum-industry, Interfaces, 20, 117-127, (1990)
[26] Bonner, Moore I (1979) Refinery and petrochemical modeling system (RPMS): a system description. Bonner & Moore Management Science, Houston
[27] Centre for Process Integration UoM (2013) REFOPT. http://www.ceas.manchester.ac.uk/media/eps/schoolofchemicalengineeringandanalyticalscience/content/researchall/centres/processintegration/REFORT.pdf. Accessed 7 Aug 2013
[28] Charnes, A; Cooper, WW; Mellon, B, Blending aviation gasoline—a study in programming interdependent activities in an integrated oil company, Econometrica, 20, 135-139, (1952)
[29] Chen, X; Grossmann, I; Zheng, L, A comparative study of continuous-time models for scheduling of crude oil operations in inland refineries, Comput Chem Eng, 44, 141-167, (2012)
[30] Cutler CR, Ramaker BL (1979) DMC—a computer control algorithm. Paper presented at the AIChE 1979 Houston meeting, Houston
[31] Cutler CR, Ramaker BL (1980) Dynamic matrix control—a computer control algorithm. Paper presented at the joint automatic control conference preprints, San Francisco
[32] Daichendt, MM; Grossmann, IE, Integration of hierarchical decomposition and mathematical programming for the synthesis of process flowsheets, Comput Chem Eng, 22, 147-175, (1998)
[33] Darby, ML; Nikolaou, M, MPC: current practice and challenges, Control Eng Pract, 20, 328-342, (2012)
[34] Darby, ML; Nikolaou, M; Jones, J; Nicholson, D, RTO: an overview and assessment of current practice, J Process Control, 21, 874-884, (2011)
[35] Dewitt, CW; Lasdon, LS; Waren, AD; Brenner, DA; Melhem, SA, OMEGA: an improved gasoline blending system for texaco, Interfaces, 19, 85-101, (1989)
[36] Elkamel, A; Ba-Shammakh, M; Douglas, P; Croiset, E, An optimization approach for integrating planning and CO_{2} emission reduction in the petroleum refining industry, Ind Eng Chem Res, 47, 760-776, (2008)
[37] Engell, S, Feedback control for optimal process operation, J Process Contr, 17, 203-219, (2007)
[38] Escudero, LF; Quintana, FJ; Salmeron, J, CORO, a modeling and an algorithmic framework for oil supply, transformation and distribution optimization under uncertainty, Eur J Oper Res, 114, 638-656, (1999) · Zbl 0938.90019
[39] Fatora F, Adams J (1998) CLRTO at Lyondell-Citgo Refining. Paper presented at the AspenTech advanced control and optimization users group meeting 1998
[40] Fernandes, LJ; Relvas, S; Barbosa-Póvoa, AP, Strategic network design of downstream petroleum supply chains: single versus multi-entity participation, Chem Eng Res Des, 91, 1557-1587, (2013)
[41] Floudas, CA; Lin, X, Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review, Comput Chem Eng, 28, 2109-2129, (2004)
[42] Furman, KC; Jia, Z; Ierapetritou, MG, A robust event-based continuous time formulation for tank transfer scheduling, Ind Eng Chem Res, 46, 9126-9136, (2007)
[43] Garvin, WW; Crandall, HW; John, JB; Spellmann, RA, Applications of linear programming in the oil industry, Manag Sci, 3, 407-430, (1957) · Zbl 0995.90627
[44] Glismann, K; Gruhn, G, Short-term scheduling and recipe optimization of blending processes, Comput Chem Eng, 25, 627-634, (2001)
[45] Gothe-Lundgren, M; Lundgren, JT; Persson, JA, An optimization model for refinery production scheduling, Int J Prod Econ, 78, 255-270, (2002)
[46] Guerra, OJ; Roux, GAC, Improvements in petroleum refinery planning: 1. formulation of process models, Ind Eng Chem Res, 50, 13403-13418, (2011)
[47] Hamisu, AA; Kabantiok, S; Wang, M, Refinery scheduling of crude oil unloading with tank inventory management, Comput Chem Eng, 55, 134-147, (2013)
[48] Hart WD (1978) L.P. Behavior—recursion example comments. ACM SIGMAP Bull 25:29-32
[49] Haverly, CA, Studies of the behavior of recursion for the pooling problem, ACM SIGMAP Bull, 25, 19-28, (1978)
[50] Haverly, CA, Behavior of recursion model-more studies, ACM SIGMAP Bull, 26, 22-28, (1979)
[51] Haverly, CA, Recursion model behavior: more studies, ACM SIGMAP Bull, 28, 39-41, (1980)
[52] Haverly, CA, OMNI model management system, Ann Oper Res, 104, 127-140, (2001) · Zbl 1007.90001
[53] Haverly Systems (2012) GRTMPS (G4). http://www.haverly.com/main-products/13-products/9-grtmps. Accessed 9 May 2012
[54] Haverly Systems (2013a) Haverly products. http://www.haverly.com/product.htm. Accessed 11 July 2013
[55] Haverly Systems (2013b) OmniSuite\^{}{®} Product Page. http://www.haverly.com/OmniSuite.htm. Accessed 10 July 2013
[56] Hofferl, F; Steinschorn, D, A dynamic programming extension to the steady state refinery-LP, Eur J Oper Res, 197, 465-474, (2009) · Zbl 1159.90504
[57] Hooker, J, A hybrid method for the planning and scheduling, Constraints, 10, 385-401, (2005) · Zbl 1122.90054
[58] Hooker, JN; Yan, H; Grossmann, IE; Raman, R, Logic cuts for processing networks with fixed charges, Comput Oper Res, 21, 265-279, (1994) · Zbl 0789.90057
[59] Iancu, M; Cristea, MV; Agachi, PS, Retrofit design of heat exchanger network of a fluid catalytic cracking plant and control based on MPC, Comput Chem Eng, 49, 205-216, (2013)
[60] Industrial Algorithms (2016) IMPL (industrial modeling and programming language). http://www.industrialgorithms.com/
[61] Ingenious (2016a) ProPlan 5.0: refinery and petrochemical planning software. http://www.ingeniousinc.com/proplan.aspx
[62] Ingenious (2016b) ProSched 5.0: refinery and petrochemical scheduling software. http://www.ingeniousinc.com/prosched.aspx
[63] Jain, V; Grossmann, IE, Algorithms for hybrid MILP/CP models for a class of optimization problems, Informs J Comput, 13, 258-276, (2001) · Zbl 1238.90106
[64] Jia, ZY; Ierapetritou, M, Mixed-integer linear programming model for gasoline blending and distribution scheduling, Ind Eng Chem Res, 42, 825-835, (2003)
[65] Jia, ZY; Ierapetritou, M, Efficient short-term scheduling of refinery operations based on a continuous time formulation, Comput Chem Eng, 28, 1001-1019, (2004)
[66] Jia, ZY; Ierapetritou, M; Kelly, JD, Refinery short-term scheduling using continuous time formulation: crude-oil operations, Ind Eng Chem Res, 42, 3085-3097, (2003)
[67] Joffe B, Kunt T, Varvarezos DK, Paules GE (2005a) PIMS advanced optimization technology. In: PIMS users conference, Madrid
[68] Joffe B, Varvarezos D, Paules G, Kunt T, Floudas CA (2005b) Global optimization in refinery planning. In: AIChE annual meeting and fall showcase, Cincinnati, Ohio, 30 October-4 November 2005, p 7339
[69] Joly, M; Pinto, J, Mixed-integer programming techniques for the scheduling of fuel oil and asphalt production, Trans IChemE Part A, 81, 427-447, (2003)
[70] Joly, M; Moro, LFL; Pinto, JM, Planning and scheduling for petroleum refineries using mathematical programming, Braz J Chem Eng, 19, 207-228, (2002)
[71] Jones, C; Baker, TE, MIMI/G: a graphical environment for mathematical programming and modeling, Interfaces, 26, 90-106, (1996)
[72] Kadam JV, Marquardt W (2007) Integration of economical optimization and control for intentionally transient process operation. Lecture notes in control and information sciences, vol 358, pp 419-434
[73] Karuppiah, R; Furman, KC; Grossmann, IE, Global optimization for scheduling refinery crude oil operations, Comput Chem Eng, 32, 2745-2766, (2008)
[74] KBC Advanced Technologies (2013a) FCC-SIM. http://www.kbcat.com/sim-suite-models/fcc-sim. Accessed 15 Apr 2013
[75] KBC Advanced Technologies (2013b) Petro-SIM refining-KBC advanced technologies. http://www.kbcat.com/process-simulation-software/petro-sim-refining. Accessed 12 Aug 2013
[76] Kelly, JD; Mann, JL, Crude oil blend scheduling optimization: an application with multimillion dollar benefits - part 1 - the ability to schedule the crude oil blendshop more effectively provides substantial downstream benefits, Hydrocarb Process, 82, 47-53, (2003)
[77] Kelly, JD; Mann, JL, Crude oil blend scheduling optimization: an application with multimillion dollar benefits - part 2 - the ability to schedule the crude oil blendshop more effectively provides substantial downstream benefits, Hydrocarb Process, 82, 72-79, (2003)
[78] Khor, CS, Stochastic programming with tractable Mean-risk objectives for planning under uncertainty, J Appl Sci, 10, 2618-2622, (2010)
[79] Khor, CS; Elkamel, A, Superstructure optimization for oil refinery design, Pet Sci Technol, 28, 1457-1465, (2010)
[80] Khor, CS; Elkamel, A; Riazi, MR (ed.); Eser, S (ed.); Diez, JLP (ed.); Agrawal, SS (ed.), Roles of computers in petroleum refineries, No. 58, 685-700, (2013), Conshohocken
[81] Khor, CS; Elkamel, A; Douglas, PL, Stochastic refinery planning with risk management, Pet Sci Technol, 26, 1726-1740, (2008)
[82] Khor, CS; Elkamel, A; Ponnambalam, K; Douglas, PL, Two-stage stochastic programming with fixed recourse via scenario planning with economic and operational risk management for petroleum refinery planning under uncertainty, Chem Eng Process, 47, 1744-1764, (2008)
[83] Khor, CS; Yeoh, XQ; Shah, N, Optimal design of petroleum refinery topology using a discrete optimization approach with logical constraints, J Appl Sci, 10, 2618-2622, (2010)
[84] Kocis, GR; Grossmann, IE, A modeling and decomposition strategy for the MINLP optimization of process flowsheets, Comput Chem Eng, 13, 797-819, (1989)
[85] Kong M-T (2002) Downstream oil products supply chain optimisation. Imperial College, London
[86] Kong, M-T; Shah, N, Preprocessing rules for integer programming solutions to the generalised assignment problem, J Oper Res Soc, 52, 567-575, (2001) · Zbl 1176.90359
[87] Koo, LY; Adhitya, A; Srinivasan, R; Karimi, IA, Decision support for integrated refinery supply chains part 2. design and operation, Comput Chem Eng, 32, 2787-2800, (2008)
[88] Kunt T, Grupa M, Varvarezos DK (2008) Integrating refinery production planning with primary and secondary distribution network optimization. Paper presented at the 5th international conference on foundations of computer-aided process operations (FOCAPO 2008), Massachusetts, USA
[89] Lasdon L, Joffe B (1990) The relationship between distributive recursion and successive linear programming in refining production planning models. In: National Petroleum Refiners Association (NPRA) computer conference, Seattle, Washington
[90] Lee, HM; Pinto, JM; Grossmann, IE; Park, S, Mixed-integer linear programming model for refinery short-term scheduling of crude oil unloading with inventory management, Ind Eng Chem Res, 35, 1630-1641, (1996)
[91] Li, J; Karimi, IA, Scheduling gasoline blending operations from recipe determination to shipping using unit slots, Ind Eng Chem Res, 50, 9156-9174, (2011)
[92] Li, WK; Hui, CW; Hua, B; Tong, ZX, Scheduling crude oil unloading, storage, and processing, Ind Eng Chem Res, 41, 6723-6734, (2002)
[93] Li, WK; Hui, CW; Li, P; Li, AX, Refinery planning under uncertainty, Ind Eng Chem Res, 43, 6742-6755, (2004)
[94] Li, WK; Hui, CW; Li, AX, Integrating CDU, FCC and product blending models into refinery planning, Comput Chem Eng, 29, 2010-2028, (2005)
[95] Li, J; Li, W; Karimi, IA; Srinivasan, R, Improving the robustness and efficiency of crude scheduling algorithms, AIChE J, 53, 2659-2680, (2007)
[96] Li, WK; Hui, CW; Karimi, IA; Srinivasan, R, A novel CDU model for refinery planning, Asia Pac J Chem Eng, 2, 282-293, (2007)
[97] Li, J; Karimi, IA; Srinivasan, R, Recipe determination and scheduling of gasoline blending operations, AIChE J, 56, 441-465, (2010)
[98] Li, J; Misener, R; Floudas, CA, Continuous-time modeling and global optimization approach for scheduling of crude oil operations, AIChE J, 58, 205-226, (2012)
[99] Li, J; Misener, R; Floudas, CA, Scheduling of crude oil operations under demand uncertainty: a robust optimization framework coupled with global optimization, AIChE J, 58, 2373-2396, (2012)
[100] Magalhães MV, Shah N (2003) Crude oil scheduling. Paper presented at the FOCAPO
[101] Mahalec V, Marlin T (2006) Real-time economic optimization (RTO) of process operations: the long road to a commercial success. Paper presented at the Canadian society of chemical engineers
[102] Manne A (1956) Scheduling of petroleum refinery operations, vol 48. Harvard University Press, Harvard Economic Studies, Cambridge
[103] Manne, A, A linear programming model of the US petroleum refining industry, Econometrica, 26, 67-106, (1958)
[104] Maravelias, CT; Grossmann, IE, A hybrid MILP/CP decomposition approach for the continuous time scheduling of multipurpose batch plants, Comput Chem Eng, 28, 1921-1949, (2004)
[105] Mendez, CA; Grossmann, IE; Harjunkoski, I; Kabore, P, A simultaneous optimization approach for off-line blending and scheduling of oil-refinery operations, Comput Chem Eng, 30, 614-634, (2006)
[106] Menezes, BC; Kelly, JD; Grossmann, IE; Vazacopoulos, A, Generalized capital investment planning of oil-refineries using MILP and sequence-dependent setups, Comput Chem Eng, 80, 140-154, (2015)
[107] Meyer, CA; Floudas, CA, Global optimization of a combinatorially complex generalized pooling problem, AIChE J, 52, 1027-1037, (2006)
[108] Misener, R; Floudas, CA, ANTIGONE: algorithms for continuous/integer global optimization of nonlinear equations, J Glob Optim, 59, 503-526, (2014) · Zbl 1301.90063
[109] Moro, LFL; Pinto, JM, Mixed-integer programming approach for short-term crude oil scheduling, Ind Eng Chem Res, 43, 85-94, (2004)
[110] Moro, LFL; Zanin, AC; Pinto, JM, A planning model for refinery diesel production, Comput Chem Eng, 22, s1039-s1042, (1998)
[111] Mouret, S; Grossmann, IE; Pestiaux, P, A novel priority-slot based continuous-time formulation for crude-oil scheduling problems, Ind Eng Chem Res, 48, 8515-8528, (2009)
[112] Mouret, S; Grossmann, IE; Pestiaux, P, A new Lagrangian decomposition approach applied to the integration of refinery planning and crude-oil scheduling, Comput Chem Eng, 35, 2750-2766, (2011)
[113] Mudt, DR; Pedersen, CC; Jett, MD; Karur, S; McIntyre, B; Robinson, PR; Hsu, CS (ed.); Robinson, PR (ed.), Refinery-wide optimization with rigorous models, No. 2, 371-392, (2006), New York
[114] Mulvey, JM; Vanderbei, RJ; Zenios, SA, Robust optimization of large-scale systems, Oper Res, 43, 264-281, (1995) · Zbl 0832.90084
[115] Neiro, SMS; Pinto, JM, A general modeling framework for the operational planning of petroleum supply chains, Comput Chem Eng, 28, 871-896, (2004)
[116] Neiro, SMS; Pinto, JM, Multiperiod optimization for production planning of petroleum refineries, Chem Eng Commun, 192, 62-88, (2005)
[117] Niederberger J, Zech IA, Silva JAD, Mizutani FT, Aires JSDS (2005) PETROX—PETROBRAS’ process simulator. Paper presented at the 2nd mercosur congress on chemical engineering and 4th mercosur congress on process systems engineering, Rio de Janeiro · Zbl 0938.90019
[118] Palmer KH, Boudwin NK, Patton HA, Sammes JD, Rowland AJ, Smith DM (1984) A model-management framework for mathematical programming. Wiley, New York · Zbl 0643.90098
[119] Pantelides, CC; Renfro, JG, The online use of first-principles models in process operations: review, current status and future needs, Comput Chem Eng, 51, 136-148, (2013)
[120] Park, J; Park, S; Yun, C; Kim, Y, Integrated model for financial risk management in refinery planning, Ind Eng Chem Res, 49, 374-380, (2010)
[121] Pedersen CC, Mudt DR, Bailey JK, Ayala JS (1995) Closed loop real time optimization of a hydrocracker complex. In: National petroleum refiners association (npra) computer conference CC-95-121, Nashville, Tennessee, 6-8 Nov 1995
[122] Persson, JA; Gothe-Lundgren, M, Shipment planning at oil refineries using column generation and valid inequalities, Eur J Oper Res, 163, 631-652, (2005) · Zbl 1071.90508
[123] Pinto, JM; Grossmann, IE, A continuous time mixed integer linear programming model for short term scheduling of multistage batch plants, Ind Eng Chem Res, 34, 3037-3051, (1995)
[124] Pinto, JM; Joly, M; Moro, LFL, Planning and scheduling models for refinery operations, Comput Chem Eng, 24, 2259-2276, (2000)
[125] Pitty, SS; Li, WK; Adhitya, A; Srinivasan, R; Karimi, IA, Decision support for integrated refinery supply chains part 1. dynamic simulation, Comput Chem Eng, 32, 2767-2786, (2008)
[126] Pongsakdi, A; Rangsunvigit, P; Siemanond, K; Bagajewicz, MJ, Financial risk management in the planning of refinery operations, Int J Prod Econ, 103, 64-86, (2006)
[127] Pontes, KV; Wolf, IJ; Embiruçu, M; Marquardt, W, Dynamic real-time optimization of industrial polymerization processes with fast dynamics, Ind Eng Chem Res, 54, 11881-11893, (2015)
[128] PRINCEPS (2016a) Flowers refinery scheduling solution. http://www.princeps.com/refinery-scheduling-solution/
[129] PRINCEPS (2016b) PrincepsLP refinery planning solution. http://www.princeps.com/refinery-planning-solution/
[130] Quesada, I; Grossmann, IE, Global optimization of bilinear process networks with multicomponent flows, Comput Chem Eng, 19, 1219-1242, (1995)
[131] Raman, R; Grossmann, IE, Modeling and computational techniques for logic-based integer programming, Comput Chem Eng, 18, 563-578, (1994)
[132] Reddy, CPP; Karimi, IA; Srinivasan, R, A new continuous-time formulation for scheduling crude oil operations, Chem Eng Sci, 59, 1325-1341, (2004)
[133] Reddy, PCP; Karimi, IA; Srinivasan, R, Novel solution approach for optimizing crude oil operations, AIChE J, 50, 1177-1197, (2004)
[134] Rigby, B; Lasdon, LS; Waren, AD, The evolution of texaco’s blending systems: from OMEGA to starblend, Interfaces, 25, 64-83, (1995)
[135] Rocha, R; Grossmann, IE; Aragao, MVSP, Petroleum allocation at PETROBRAS: mathematical model and a solution algorithm, Comput Chem Eng, 33, 2123-2133, (2009)
[136] Saharidis, GKD; Ierapetritou, MG, Scheduling of loading and unloading of crude oil in a refinery with optimal mixture preparation, Ind Eng Chem Res, 48, 2624-2633, (2009)
[137] Saharidis, GKD; Minoux, M; Dallery, Y, Scheduling of loading and unloading of crude oil in a refinery using event-based discrete time formulation, Comput Chem Eng, 33, 1413-1426, (2009)
[138] Sear, TN, Logistics planning in the downstream oil industry, J Oper Res Soc, 44, 9-17, (1993)
[139] Shah, N, Mathematical programming techniques for crude oil scheduling, Comput Chem Eng, 20, s1227-s1232, (1996)
[140] Shah, NK; Ierapetritou, MG, Short-term scheduling of a large-scale oil-refinery operations: incorporating logistics details, AIChE J, 57, 1570-1584, (2011)
[141] Shah, N; Saharidis, GKD; Jia, ZY; Ierapetritou, MG, Centralized-decentralized optimization for refinery scheduling, Comput Chem Eng, 33, 2091-2105, (2009)
[142] Shah, NK; Li, ZK; Ierapetritou, MG, Petroleum refining operations: key issues, advances, and opportunities, Ind Eng Chem Res, 50, 1161-1170, (2011)
[143] Sherali, HD; Alameddine, A, A new reformulation linearization technique for bilinear programming problems, J Glob Optim, 2, 379-410, (1992) · Zbl 0791.90056
[144] Sildir H, Arkun Y, Cakal B, Gokce D, Kuzu E (2012) Real-time optimization of an industrial hydrocracking plant. Paper presented at the 2012 AIChE annual meeting (AIChE 2012) Pittsburgh, 28 October 2012-2 November 2012
[145] Soteica Visual Mesa (2015) VisualMesa petroleum refining and terminals solution. http://svmesa.com/refining-terminals.php
[146] Steinschorn D, Hofferl F (1997) Refinery scheduling using mixed integer LP and dynamic recursion. In: NPRA computer conference, New Orleans · Zbl 1159.90504
[147] Symonds GH (1955) Linear programming: the solution of refinery problems. Esso Standard Oil Company, New York
[148] Tawarmalani M, Sahinidis NV (2002) Convexification and global optimization in continuous and mixed-integer nonlinear programming: theory, algorithms, software, and applications. Nonconvex Optimization and Its Applications, vol 65. Kluwer Academic Publishers, Dordrecht · Zbl 1031.90022
[149] Thomas C, Tong D, Jasper D, Acuff C (2009) Agile supply chain planning. Hydrocarb Process October 2009.
[150] Ugray, Z; Lasdon, L; Plummer, JC; Bussieck, M, Dynamic filters and randomized drivers for the multi-start global optimization algorithm MSNLP, Optim Method Softw, 24, 635-656, (2009) · Zbl 1180.90250
[151] Varvarezos, DK, Optimal solution-range analysis in production planning: refinery feedstock selection, Ind Eng Chem Res, 47, 8282-8285, (2008)
[152] Varvarezos D (2013a) Personal communication with Mel Bernstein
[153] Varvarezos D (2013b) Refinery optimization-recent advances in planning and blending operations. Paper presented at the fields industrial optimization seminar (invited presentation), The Fields Institute for Research in Mathematical Sciences, Toronto, Canada, March 2013
[154] Varvarezos DK (2013c) Personal communication with Mikkel Sorensen. Austria
[155] Varvarezos D, Janak S (2012) Rundown blending optimization: a novel approach to a challenging scheduling problem. In: 6th international conference on foundations of computer-aided process operations (FOCAPO 2012), Savannah, 8-13 Jan 2012
[156] Viswanathan, J; Grossmann, IE, A combined penalty function and outer-approximation method for MINLP optimization, Comput Chem Eng, 14, 769-782, (1990)
[157] Wächter, A; Biegler, LT, On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Math Program, 106, 25-57, (2006) · Zbl 1134.90542
[158] Wang, K; Shao, Z; Biegler, LT; Lang, Y; Qian, J, Robust extensions for reduced-space barrier NLP algorithms, Comput Chem Eng, 35, 1994-2004, (2011)
[159] Yadav, S; Shaik, MA, Short-term scheduling of refinery crude oil operations, Ind Eng Chem Res, 51, 9287-9299, (2012)
[160] Zanin, AC; Gouvea, MT; Odloak, D, Industrial implementation of a real-time optimization strategy for maximizing production of LPG in a FCC unit, Comput Chem Eng, 24, 525-531, (2000)
[161] Zanin, AC; Gouvea, MT; Odloak, D, Integrating real-time optimization into the model predictive controller of the FCC system, Control Eng Pract, 10, 819-831, (2002)
[162] Zhang, J; Zhu, XX; Towler, GP, A level-by-level debottlenecking approach in refinery operation, Ind Eng Chem Res, 40, 1528-1540, (2001)
[163] Zhang, J; Zhu, XX; Towler, GP, A simultaneous optimization strategy for overall integration in refinery planning, Ind Eng Chem Res, 40, 2640-2653, (2001)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.