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OMEGA: An Improved Gasoline Blending System for Texaco

Author

Listed:
  • Calvin W. DeWitt

    (Computer and Information Systems Department, Eastern New Mexico University, Portales, New Mexico 88130)

  • Leon S. Lasdon

    (Management Science and Information Systems Department, University of Texas, Austin, Texas 78712)

  • Allan D. Waren

    (Computer and Information Science Department, Cleveland State University, Cleveland, Ohio 44115)

  • Donald A. Brenner

    (Refining Department, Texaco Inc., Houston, Texas 77052)

  • Simon A. Melhem

    (Information Technology Department, Texaco Inc., Houston, Texas 77237)

Abstract

Gasoline blending is a critical refinery operation. In 1980, Texaco began developing an improved, optimization based, decision support system for planning and scheduling its blending operations. The system, OMEGA, is implemented on personal computers and on larger computer systems. It relies on refinery data bases and on-line data acquisition and exploits detailed nonlinear models of gasoline attributes. Texaco uses OMEGA in all seven US refineries and its Canadian and Welsh refineries. Its benefits include an estimated $30 million annually, better quality control, improved planning and marketing information, and the ability to conduct a variety of what-if studies.

Suggested Citation

  • Calvin W. DeWitt & Leon S. Lasdon & Allan D. Waren & Donald A. Brenner & Simon A. Melhem, 1989. "OMEGA: An Improved Gasoline Blending System for Texaco," Interfaces, INFORMS, vol. 19(1), pages 85-101, February.
    • Handle: RePEc:inm:orinte:v:19:y:1989:i:1:p:85-101
    DOI: 10.1287/inte.19.1.85
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    Citations

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    Cited by:

    1. Yifu Chen & Christos T. Maravelias, 2020. "Preprocessing algorithm and tightening constraints for multiperiod blend scheduling: cost minimization," Journal of Global Optimization, Springer, vol. 77(3), pages 603-625, July.
    2. Mohammed Alfaki & Dag Haugland, 2014. "A cost minimization heuristic for the pooling problem," Annals of Operations Research, Springer, vol. 222(1), pages 73-87, November.
    3. Charles Audet & Jack Brimberg & Pierre Hansen & Sébastien Le Digabel & Nenad Mladenovi'{c}, 2004. "Pooling Problem: Alternate Formulations and Solution Methods," Management Science, INFORMS, vol. 50(6), pages 761-776, June.
    4. Ted Kutz & Mark Davis & Robert Creek & Nick Kenaston & Craig Stenstrom & Margery Connor, 2014. "Optimizing Chevron’s Refineries," Interfaces, INFORMS, vol. 44(1), pages 39-54, February.
    5. Yifu Chen & Christos T. Maravelias, 2022. "Variable Bound Tightening and Valid Constraints for Multiperiod Blending," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2073-2090, July.
    6. Draman, Murat & Kuban Altinel, I & Bajgoric, Nijaz & Tamer Unal, Ali & Birgoren, Burak, 2002. "A clone-based graphical modeler and mathematical model generator for optimal production planning in process industries," European Journal of Operational Research, Elsevier, vol. 137(3), pages 483-496, March.
    7. Gothe-Lundgren, Maud & T. Lundgren, Jan & A. Persson, Jan, 2002. "An optimization model for refinery production scheduling," International Journal of Production Economics, Elsevier, vol. 78(3), pages 255-270, August.
    8. Natashia Boland & Thomas Kalinowski & Fabian Rigterink, 2017. "A polynomially solvable case of the pooling problem," Journal of Global Optimization, Springer, vol. 67(3), pages 621-630, March.
    9. Radu Baltean-Lugojan & Ruth Misener, 2018. "Piecewise parametric structure in the pooling problem: from sparse strongly-polynomial solutions to NP-hardness," Journal of Global Optimization, Springer, vol. 71(4), pages 655-690, August.
    10. Chang, Jiyoun C. & Graves, Stephen C. & Kirchain, Randolph E. & Olivetti, Elsa A., 2019. "Integrated planning for design and production in two-stage recycling operations," European Journal of Operational Research, Elsevier, vol. 273(2), pages 535-547.
    11. Dimitri J. Papageorgiou & Alejandro Toriello & George L. Nemhauser & Martin W. P. Savelsbergh, 2012. "Fixed-Charge Transportation with Product Blending," Transportation Science, INFORMS, vol. 46(2), pages 281-295, May.
    12. Dag Haugland & Eligius M. T. Hendrix, 2016. "Pooling Problems with Polynomial-Time Algorithms," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 591-615, August.

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