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A dynamic programming extension to the steady state refinery-LP

Author

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  • Höfferl, F.
  • Steinschorn, D.

Abstract

Standard LPs, widely used for planning in the processing industry, are powerful tools for making economic decisions, but do not cover time relationships inside the planning timeframe. To include sequence-dependent issues within the optimization process, an algorithmic extension to the LP was developed. DPX (Dynamic Programming Extension) is used to solve a whole class of problems that are dynamic in time.

Suggested Citation

  • Höfferl, F. & Steinschorn, D., 2009. "A dynamic programming extension to the steady state refinery-LP," European Journal of Operational Research, Elsevier, vol. 197(2), pages 465-474, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:2:p:465-474
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    References listed on IDEAS

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    1. Alan S. Manne, 1960. "Linear Programming and Sequential Decisions," Management Science, INFORMS, vol. 6(3), pages 259-267, April.
    2. Chryssolouris, George & Papakostas, Nikolaos & Mourtzis, Dimitris, 2005. "Refinery short-term scheduling with tank farm, inventory and distillation management: An integrated simulation-based approach," European Journal of Operational Research, Elsevier, vol. 166(3), pages 812-827, November.
    3. D. P. de Farias & B. Van Roy, 2003. "The Linear Programming Approach to Approximate Dynamic Programming," Operations Research, INFORMS, vol. 51(6), pages 850-865, December.
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