Phenomenological Decomposition Heuristic for Process Design Synthesis of Oil-Refinery Units

We propose a mixed-integer nonlinear optimization for process design synthesis of oil-refinery units that includes crude-oil mixing, unit processing and product blending. The quantity-logic-quality phenomena involving a non-convex mixed-integer nonlinear problem is decomposed into a two-stage stochastic programming model with complete recourse considering, in a first stage, quantity and logic variables in a mixed-integer linear model and, in a second stage, quantity and quality variables in a nonlinear programming formulation. Iteratively, nonlinear models of each demand scenario are restricted by the multi-scenario process design results. An industrial-sized example that is not solved in a full space model demonstrates our tailor-made decomposition scheme, which yields within 5% gap between the first and the average second stage results.