A priority-slot based continuous-time formulation for crude-oil scheduling problems with oil residency time constraint

A priority-slot based continuous-time formulation for crude-oil scheduling problems with oil residency time constraint

Yuming ZhaoNaiqi Wu 

School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou 510006, Guangdong, China

School of Computer Science, Zhaoqing University, Zhaoqing 526061, Guangdong, China

Corresponding Author Email: 
ymzhao@zqu.edu.cn
Page: 
22-30
|
DOI: 
https://doi.org/10.18280/rces.040105
Received: 
| |
Accepted: 
| | Citation

OPEN ACCESS

Abstract: 

The optimal scheduling of crude-oil operation in refineries has been studied by various groups during the past decade leading to different mixed integer linear programming or mixed nonlinear programming formulations. This paper presents a new formulation with oil residency time constraint based on single-operation sequencing (SOS). At the same time, the bilinear constraints in the formulation are replaced by its necessary conditions, which are linear. A simple MILP-NLP procedure has been used to solve this model and leads to a satisfactory optimal result.

Keywords: 

Oil Refinery, Scheduling, Continuous-Time Formulation, Residency Time Constraint.

1. Introduction
2. Process and Its Short-Term Scheduling Problem
3. Problem Formulation
4. Solution Method
5. Numerical Example
6. Conclusion
Acknowledgements
  References

[1] Wu N.Q., Chu F., Chu C.B., Zhou M.C. (2009). Short-term schedulability analysis of multiple distiller crude oil operations in refinery with oil residency time constraint, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 39, No. 1, pp. 1–16. DOI: 10.1109/TSMCC.2008.2001709

[2] Moro L.F.L. (2003). Process technology in the petroleum refining industry—Current situation and future trends, Computers & Chemical Engineering, Vol. 27, pp. 1303–1305. DOI: 10.1016/S0098-1354(03)00054-1

[3] Bechtel (1993). PIMS (Process Industry Modeling System) User’s Manual, Version 6.0, Bechtel Corporation, Houston, TX.

[4] Pelham R., Pharris C. (1996). Refinery operation and control: a future vision, Hydrocarbon Process., Vol. 75, No. 7, pp. 89–94.

[5] Baker K.R. (1974). Introduction to Sequencing and Scheduling, New York: Wiley.

[6] Chen H.X., Chu C.B., Proth J.M. (1998). An improvement of the Lagrangian relaxation approach for job shop scheduling: A dynamic programming method, IEEE Trans. on Robotics and Automation, Vol. 14, No. 5, pp. 786–795.

[7] Mattfeld D.C., Bierwirth C. (2004). An efficient genetic algorithm for job shop scheduling with tardiness objectives, European Journal of Operational Research, Vol. 155, No. 2, pp. 616–630. DOI: 10.1016/S0377-2217(03)00016-X

[8] Ponnambalam S.G., Jawahar N., Aravindan P. (1999). A simulated annealing algorithm for job shop scheduling, Production Planning & Control, Vol. 10, No. 8, pp. 767–777. DOI: 10.1080/095372899232597

[9] Sabuncuoglu I., Bayiz M. (1999). Job shop scheduling with beam search, European Journal of Operational Research, Vol. 118, No. 2, pp. 390–412. DOI: 10.1016/S0377-2217(98)00319-1

[10] Yang S.X., Wang D.W. (2001). A new adaptive neural network and heuristics hybrid approach for job-shop scheduling, Computers & Operations Research, Vol. 28, No. 10, pp. 955–971. DOI: 10.1016/S0305-0548(00)00018-6

[11] Stephanopoulos G., Han C. (1996). Intelligence systems in process engineering: a review, Computers & Chemical Engineering, Vol. 20, pp. 743–791.

[12] Murakami Y., Uchiyama H., Hasebe S., Hashimoto I. (1997). Application of repetitive SA method to scheduling problem in chemical processes, Computers & Chemical Engineering, Vol. 21, pp. 1087–1092. DOI: 10.1016/s0098-1354(97)87647-8

[13] Wu N.Q. (1999). Necessary and sufficient conditions for deadlock-free operation in flexible manufacturing systems using a colored Petri net model, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 29, No. 2, pp. 192–204. DOI: 10.1109/5326.760564

[14] Wu N.Q., Bai L.P., Chu C.B. (2004). Hybrid Petri net modeling for refinery process, in Proc. 2004 IEEE International Conference on Systems, Man, & Cybernetics, pp. 1734–1739.

[15] Wu N.Q., Bai L.P., Chu C.B. (2007). Modeling and conflict detection of crude-oil operations for refinery process based on controlled-colored timed Petri net, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 37, No. 4, pp. 461–472. DOI: 10.1109/TSMCC.2007.897339

[16] Wu N.Q., Zhou M.C., Chu F. (2005). Short-term scheduling for refinery process: bridging the gap between theory and applications, Int. J. Intelligent Control Systems, Vol. 10, No. 2, pp. 162–174. DOI: 10.1109/icsmc.2006.384561

[17] Wu N.Q., Zhou M.C., Chu F., Qian Y.M. (2006). Issues on short term scheduling of oil refinery, in Proc. 2006 IEEE International Conference on Systems, Man, & Cybernetics, Taiwan, pp. 2920–2925.

[18] Wu N.Q., Zhou M.C., Chu F. (2008). A Petri net based heuristic algorithm for realizability of target refining schedule for oil refinery, IEEE Trans. on Automation Science Engineering, Vol. 5, No. 4, pp. 661–676. DOI: 10.1109/TASE.2008.916737

[19] Wu N.Q., Chu F., Chu C.B., Zhou M.C. (2008). Short-term schedulability analysis of crude oil operations in refinery with oil residency time constraint using Petri net, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 38, No. 6, pp. 765–778. DOI: 10.1109/TSMCC.2008.2001688

[20] Wu N.Q., Chu F., Chu C.B., Zhou M.C. (2008). Short-term schedulability analysis of crude oil operations in refinery with hybrid Petri net, in Proc. 2008 IEEE International Conference on Systems, Man, & Cybernetics, Singapore, pp. 1916–1921.

[21] Wu N.Q., Chu F., Chu C.B., Zhou M.C. (2009). Short-term schedulability analysis of multiple distiller crude oil operations in refinery with oil residency time constraint, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 39, No. 1, pp. 1–16. DOI: 10.1109/TSMCC.2008.2001709

[22] Wu N.Q., Zhou M.C. (2009). System Modeling and Control with Resource-Oriented Petri Nets, New York: CRC Press, Taylor & Francis Group.

[23] Ierapetritou M.G., Floudas C.A. (1998). Effective continuous-time formulation for short-term scheduling, 1. Multipurpose batch processes, Industrial & Engineering Chemistry Research, Vol. 37, pp. 4341–4359. DOI: 10.1021/ie970927g

[24] Ierapetritou M.G., Floudas C.A. (1998). Effective continuous-time formulation for short-term scheduling. 2. Continuous and semicontinuous processes, Industrial & Engineering Chemical Research, Vol. 37, pp. 4360–4374. DOI: 10.1021/ie9709289

[25] Mendez C.A., Cerda J. (2003). Dynamic scheduling in multiproduct batch plants, Computers & Chemical Engineering, Vol. 27, pp. 1247–1259. DOI: 10.1016/s0098-1354(03)00050-4

[26] Moro L.F.L. (2003). Process technology in the petroleum refining industry—current situation and future trends, Computers & Chemical Engineering,

Vol. 27, pp. 1303–1305. DOI: 10.1016/s0098-1354(03)00054-1

[27] Pinto J.M., Grossmann I.E. (1997). A logic-based approach to scheduling problem with resource constraints, Computers & Chemical Engineering, Vol. 21, pp. 801–818. DOI: 10.1016/s0098-1354(96)00318-3

[28] Shobrys D.E., White D.C. (2000). Planning, scheduling and control systems: why can they not work together, Computers & Chemical Engineering, Vol. 24, pp. 63-173. DOI: 10.1016/s0098-1354(00)00508-1

[29] Gabbar H.A. (2007). Synthesis of parallel operation for enhanced chemical plant operation, IEEE Trans. on Systems, Man, & Cybernetics, Part C, Vol. 37, No. 4, pp. 703–711. DOI: 10.1109/TSMCC.2007.897441

[30] Kallrath J. (2002). Planning and scheduling in the process industry. OR Spectrum, Vol. 24, pp. 219–250.

[31] Baptiste P., Le Pape C., Nuijten W. (2001). Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems, Kluwer Academic Publishers: Norwell, MA.

[32] Floudas C.A., Lin X. (2004). Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review, Computers & Chemical Engineering, Vol. 28, pp. 2109–2129. DOI: 10.1016/j.compchemeng.2004.05.002

[33] Mendez C.A., Grossmann I.E., Harjunkoski I., Kabore P. (2006). A simultaneous optimization approach for off-line blending and scheduling of oil-refinery operations, Computers & Chemical Engineering, Vol. 30, pp. 614–634. DOI: 10.1016/j.compchemeng.2005.11.004

[34] Kondili E., Pantelides C.C., Sargent R.W.H. (1993). A general algorithm for short-term scheduling of batch operations. I: MILP formulation, Computers & Chemical Engineering, Vol. 17, pp. 211–227. DOI: 10.1016/0098-1354(93)80015-f

[35] Pantelides C.C. (1994). Unified frameworks for optimal process planning and scheduling, Proc. Second Int. Conf. Found. Computer-Aided Process Operat., pp. 253-274.

[36] Zhang X., Sargent R.W.H. (1998). The optimal operation of mixed production facilities - extensions and improvements, Computers & Chemical Engineering, Vol. 22, pp. 1287-1295.

[37] Schilling G., Pantelides C.C. (1996). A simple continuous-time process scheduling formulation and a novel solution algorithm, Computers & Chemical Engineering, Vol. 20, pp. S1221–S1226.

[38] Mouret S., Grossmann I., Pestiaux P. (2009). A novel priority-slot based continuous-time formulation for crude-oil scheduling problems, Industrial and Engineering Chemistry Research, Vol. 48, No. 18, pp. 8515-8528. DOI: 10.1021/ie8019592