Possibility FCC Models for Crude Oil Scheduling and Storage Management

Abstract

This paper develops three kinds of possibility fuzzy chance constrained (PFCC) mixed-integer nonlinear programming models (MINLP) and the solution methods for the integrated problem of refinery short-term crude oil scheduling and storage management under demands uncertainty of CDUs (Crude-oil Distillation Units). To reduce the calculation complexity of these models, they are transformed into its equivalent fuzzy chance constrained mixed-integer linear programming (PFCC-MILP) models by using the method of Quesada & Grossmann [1995]. After that these PFCC-MILP models are solved through their crisp equivalent algorithm and fuzzy simulation algorithms rely on the theory presented by Liu & Iwamura [1998] for the first time in this area. Finally, a case study which has 265 continuous variables, 68 binary variables and 318 constraints is effectively solved in LINGO 8.0 [Xie et al., 2005] with the proposed approaches.