In this paper a comparison of some of the methods available for solving mixed integer non-linear programming (MINLP) problems is presented. Since some methods solve both a mixed integer linear programming (MILP) master problem and non-linear programming (NLP) subproblems during the iterations, while others only solve MILP master problems, a comparison of the computer resources needed for the optimization is presented. The methods are applied on a number of significant chemical engineering problems involving both MINLP problems (with a variety in the degree of discreteness and complexity) and some strict integer non-linear programming (INLP) problems. From the results, it is to be seen that a comparison of only the number of iterations needed in the optimization, doesn't allways measure the actual required resources of the optimization.
|Journal||Computers and Chemical Engineering|
|Publication status||Published - 1996|
|MoE publication type||A2 Review article in a scientific journal|
- Design Optimization
- Mathematical Programming
- Process Integration
- Process Synthesis