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Chance Constrained Programming with Fuzzy Parameters for Refinery Crude Oil Scheduling Problem

  • Cuiwen Cao
  • Xingsheng Gu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

Abstract

The main objective of this work is to put forward a chance constrained mixed-integer nonlinear fuzzy programming model for refinery short-term crude oil scheduling problem under demands uncertainty of distillation units. The model studied has characteristics of discrete events and continuous events coexistence, multistage, multiproduct, uncertainty and large scale. Firstly, the model is transformed into its equivalent fuzzy mixed-integer linear programming model by using the method of Quesada & Grossmann [5]. Then the fuzzy equivalent model is changed into its crisp MILP model relies on the theory presented by Liu & Iwamura [12] for the first time in this area. Finally, the crisp MILP model is solved in LINGO 8.0 based on time discretization. A case study which has 265 continuous variables, 68 binary variables and 318 constraints is effectively solved with the proposed solution approach.

Keywords

Storage Tank Distillation Unit Demand Uncertainty Chance Constraint Fuzzy Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Cuiwen Cao
    • 1
  • Xingsheng Gu
    • 1
  1. 1.Research Institute of AutomationEast China University of Science and TechnologyShanghaiChina

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