By many financial and physical measures, the petroleum industry is the world’s largest industry. The industry’s operations comprise a global supply chain that produces, transports, refines, and distributes more than 85 million barrels of oil per day – nearly 5 billion tons per year.
Because of its scale, global scope, and huge capital requirements, the petroleum industry is populated with many large, vertically-integrated companies (many of them national oil companies) with global operations. The industry is highly competitive because it has many participants and because it produces basic commodities (e.g., gasoline, diesel fuel, petrochemical feedstocks, etc.) that are difficult to differentiate by brand. The industry’s huge volume and low margins mean that even small changes in operating costs have important effects on operating results. The petroleum industry is a leader in the development and application of new technology; it develops and applies advanced technologies...
- Baker, T. E. (2000). Petrochemical industry. Encyclopedia of operations research and management science (2nd ed). Kluwer Academic Publishers.Google Scholar
- Baker, T. E. (1994). An integrated approach to planning and scheduling. In D. W. T. Rippin (Ed.), Foundations of computer-aided process operations (pp. 237–251). Texas: Austin. CACHE.Google Scholar
- Bodington, C. E. (1995). Planning, scheduling and control integration in the process industries. New York: McGraw-Hill.Google Scholar
- Council, N. P. (2000). U.S. Petroleum refining: Assuring the adequacy and affordability of cleaner fuels. Washington, DC: National Petroleum Council.Google Scholar
- Edgar, T. F., & Himmelblau, D. M. (1988). Optimization of chemical processes. New York: McGraw-Hill.Google Scholar
- Gary, J. H., Handwerk, G. E., & Kaiser, M. J. (2007). Petroleum refining technology and economics. Boca Raton, FL: CRC Press.Google Scholar
- Guyonnet, P., Grant, F. H., & Bagajewicz, M. J. (2009). Integrated model for refinery planning, oil procuring, and product distribution. Industrial and Engineering Chemistry Research, 48(463–482), 2009.Google Scholar
- Main, R. A. (1993). Large recursion models: Practical aspects of recursion techniques. In T. A. Ciriani & R. C. Leachman (Eds.), Optimization in industry. New York: Wiley.Google Scholar
- Maples, R. E. (2000). Petroleum refinery process economics (2nd ed.). Tulsa, Oklahoma: PennWell Corporation.Google Scholar
- Miller, D., et al. (1994). A modular system for scheduling chemical plant production. In D. W. T. Rippin (Ed.), Foundations of computer-aided process operations (pp. 355–372). Texas: Austin. CACHE.Google Scholar
- Palmer, K. H., et al. (1984). A model-management framework for mathematical programming. New York: Wiley.Google Scholar
- Pawde, M. D., & Singh, S. (2010). “Crude oil cargo selection and time frame of LP optimization,” Petroleum Technology Quarterly, Third Quarter, 2010.Google Scholar
- Symonds, G. H. (1955). Linear programming–the solution of refinery problems. New York: Esso Standard Oil Company.Google Scholar
- Tucker, M. A. (2001). “LP modeling – past, present, and future,” National Petrochemical and Refiners Association (NPRA) 2001 Computer conference, Paper CC-01-153.Google Scholar