MINLP optimization strategies and algorithms for process synthesis

This paper will attempt to show that one of the trends in the area of process synthesis is its gradual evolution towards the mathematical programming approach. This is in part due to the fundamental understanding that has been gained on the nature of the synthesis problems over the last twenty years. However, another major part has to do with the development of new and more powerful mathematical programming algorithms. In particular, the development of new MINLP algorithms, coupled with advances in computers and software, is opening promising possibilities to rigorously model, optimize and automate synthesis problems. A general overview of the MINLP approach and algorithms will be presented in this paper with the aim of gaining a basic understanding of these techniques. Strengths and weaknesses will be discussed, as well as difficulties and challenges that still need to be overcome. In particular, it will be shown how proper problem representations, effective modelling schemes and solution strategies can play a crucial role in the successful application of these techniques. The application of MINLP algorithms in process synthesis will be illustrated with several examples.