Encyclopedia of Operations Research and Management Science

2001 Edition
| Editors: Saul I. Gass, Carl M. Harris

Petro-chemical industry

Reference work entry
DOI: https://doi.org/10.1007/1-4020-0611-X_750
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Introduction

Almost from its inception, the petro-chemical industry has been dominated by very large, fully integrated, multi-national companies competing in world markets. This competitive environment has led to the application of OR/MS tools in literally all facets of the business: search and estimation techniques in exploration, production and processing optimization, and transportation and vehicle routing techniques in product delivery. In fact, it is difficult to identify an OR/MS tool or approach that has not been successfully applied in the petro-chemical industry.

During the 1960s and 1970s, most large companies in the industry maintained sizable OR/MS groups or departments with concentrations of expertise in linear programming, simulation and statistical analysis. These groups stretched the limits of the available problem-solving technologies and provided the impetus for many advancements in the OR/MS field during that era. Today, most of these central OR/MS groups have been...

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References

  1. [1]
    Baker, T.E. and Lasdon, L.S. (1985). “Successive Linear Programming at Exxon,” Management Science, 31, 264–274.Google Scholar
  2. [2]
    Baker, T.E. (1994). “An Integrated Approach to Planning and Scheduling,” Foundations of Computer-Aided Process Operations, D.W.T. Rippin, ed., CACHE, Austin, Texas, 237–251.Google Scholar
  3. [3]
    Bammi, D. (1990). “Northern Border Pipeline Logistics Simulation,” Interfaces, 20(3), 1–13.Google Scholar
  4. [4]
    Beale, E.M.L. (1978). “Nonlinear Programming Using a General Mathematical Programming System,” in Design and Implementation of Optimization Software, H.J. Greenberg, ed., Sijthoff and Noordhoff, The Netherlands, 259–279.Google Scholar
  5. [5]
    Bodington, C.E. and Baker, T.E. (1990). “A History of Mathematical Programming in the Petroleum Industry,” Interfaces, 20(3), 117–127.Google Scholar
  6. [6]
    Bodington, C.E. (1995). Planning, Scheduling and Control Integration in the Process Industries, McGraw-Hill, New York.Google Scholar
  7. [7]
    Brown, G.G., et al. (1987). “Real-Time, Wide Area Dispatch of Mobil Tank Trucks,” Interfaces, 17(1), 107–120.Google Scholar
  8. [8]
    Charnes, A., Cooper, W.W., and Mellon, B. (1952). “Blending Aviation Gasoline–A Study in Programming Interdependent Activities in an Integrated Oil Company,” Econometrica, 20(2), 135–139.Google Scholar
  9. [9]
    Ciriani, T.A. and Leachman, R.C. (1993). Optimization in Industry, John Wiley, New York.Google Scholar
  10. [10]
    de Geus, A.P. (1988). “Planning As Learning,” Harvard Business Review, 88(2), 70–77.Google Scholar
  11. [11]
    Edgar, T.F. and Himmelblau, D.M. (1988). Optimization of Chemical Processes, McGraw-Hill, New York.Google Scholar
  12. [12]
    Findlay, P.L., et al. (1989). “Optimization of the Daily Production Rates for an Offshore Oilfield,” Jl. Operational Research Society, 40, 1079–1088.Google Scholar
  13. [13]
    Griffith, R.E. and Stewart, R.A. (1961). “A Nonlinear Programming Technique for the Optimization of Continuous Processing Systems,” Management Science, 7, 379–392.Google Scholar
  14. [14]
    Hansen, P., et al. (1992). “Location and Sizing of Off-shore Platforms for Oil Exploration,” European Jl. Operational Research, 58(2), 202–214.Google Scholar
  15. [15]
    Higgins, J.G. (1993). “Planning for Risk and Uncertainty in Oil Exploration,” Long Range Planning, 26(1), 111–122.Google Scholar
  16. [16]
    Klingman, D., et al. (1987). “The Successful Deployment of Management Science Throughout Citgo Petroleum Corporation,” Interfaces, 17(1), 4–25.Google Scholar
  17. [17]
    Lasdon, L.S. and Waren, A.D. (1980). “A Survey of Nonlinear Programming Applications,” Operations Research, 28, 102–1073.Google Scholar
  18. [18]
    Manne, A. (1958). “A Linear Programming Model of the US Petroleum Refining Industry,” Econometrica, 26(1), 67–106.Google Scholar
  19. [19]
    Miller, D., et al. (1994). “A Modular System for Scheduling Chemical Plant Production,” Foundations of Computer-Aided Process Operations, D.W.T. Rippin ed., CACHE, Austin, Texas, 355–372.Google Scholar
  20. [20]
    Miller, D. (1987). “An Interactive, Computer-Aided Ship Scheduling System,” European Jl. Operational Research, 32(3), 363–379.Google Scholar
  21. [21]
    Palmer, K.H., et al. (1984). A Model-Management Framework for Mathematical Programming, John Wiley, New York.Google Scholar
  22. [22]
    Power, M. (1992). “Simulating Natural Gas Discoveries,” Interfaces, 22(2), 38–51.Google Scholar
  23. [23]
    Symonds, G.H. (1955). Linear Programming–The Solution of Refinery Problems, Esso Standard Oil Company, New York.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  1. 1.Chesapeake Decision Sciences, Inc.New ProvidenceUSA