Many optimization problems in chemical engineering involve integer variables and trade-off objective. One approach to address this type of problem is using algorithms that handle continuous and integer variables, for example, BARON algorithm (deterministic) or NSGA II (Stochastic).This matlab code is an example of Multi-Objective optimization of Aspen Plus distillation column using NSGA II algorithm.
Simulation of distillation column was carried out in Aspen Plus V8.8, because simulation time of each interation in version V9 or 10 was 10 times more than in version V8.8.

Optimization Problem Statement:
Objective Functions (2) : [min{CAPEX}, min{OPEX}]
Optimization Variables (3): [x1=Column Stages Number, x2=Reflux Ratio, x3: Normalized Column Feed Stage]
Constraints: Cons 1=Ethanol Mole Recovery > 99%; Cons 2=Ethanol Mole Purity > 80%

NSGA II Setup
Generations: 20
Population: 20
Note: Please, refer to code "Opt_EthanolColumn.m" for better understanding of NSGA algorithm parameters.

Run the code: Put all files in the same folder and run script "Opt_EthanolColumn.m"

Simulation file "ETHANOLColumn_v8.8" (Aspen Plus V.8.8) in: https://drive.google.com/open?id=1oSqqMj11h3NJlHPlhzCeok9baaH4PHnC

Please let me know any questions.

Regards,
Andrés Abril.