Optimization advanced discrete-continuous

There is a need for advanced discrete-continuous optimization tools that can handle mixed-integer, discrete-logic, and quantitative-qualitative equations to model synthesis and planning and scheduling problems. 

The MINLP problem in the TMP case is simple in that the NPV (net present value) per capital employed can be determined by first treating both the design parameters (IVRef tuid Flank) discrete ones and dien interpolating a continuous cost fimction Cost = y( Plank) for the optimal number of refiners. Consequently, no advanced MINLP solvers are needed. 

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