NEW STRATEGY AND ALGORITHM OF MODULAR BASED MINLP FOR PROCESS SYNTHESIS
This paper deals with the formulation and solution of a class of mixed-integer nonlinear programming (MINLP) problems, applied to optimal process synthesis in a modular environment. The proposed algorithm avoids doing a lot of calculation of the model equations. It makes the size of MINLP small. The MINLP algorithm consists of solving alternation sequences of MILP master problem and NLP subproblems, whose sizes are remarkably reduced. The NLP subproblem provides the linearization information of the nonlinear constraints that relate the output variables to input variables specified explicitly. The HDA process is taken as a case study of the capabilities of the process synthesizer. It proves that the proposed solution deals with complex MINLP problems satisfactory.