Mixed-integer dynamic optimization problem formulation

Note 3.3. Mixed-integer dynamic optimization problem formulation (Bansal et al., 2000 Bansal, 2000). 

Advantages i) optimization-based approaches are applicable for multiple reactions and where reactive equilibrium or thermal neutrality cannot be assured and (n) it allows the generation of optimum designs with respect to economics and controllabihty. 

Limitations (i) special care should be paid to the model formulation and the physical significance of the solution scaling of optimization variables might be required to reduce computational effort ii) the optimization problem might be difficult to solve (Hi) huge computational time can be required for multiple alternative optimizations (iv) it is difficult to perform sensitivity analysis of the optimum solution and (v) local limitations can be found when the initial guess lies outside the feasibility region. 

Systems features chemical reaction AB C D, components volatilities A/B/C/D = 4/1/8/2. (adapted from Bessling 

Short-cut methods derived from conventional distillation have been foimd to be inappropriate for the estimation of reflux ratio for reactive case and new approaches have been adopted. Methods derived from the boundary-value approach (c/. 3.2.4) allow the determination of the minimum and real reflux ratio, which are key factors in the determination of vapor and liquid velocities. The reflux ratio can be calculated using an iterative procedure, described in Subawalla and Fair (1999) and summarized in figure 3.9. 

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