Abstract

The use of the mathematical programming approach to the synthesis of chemical processes has many valuable creative principles, i.e. optimality, feasibility and integrality of solutions, which are essential for obtaining “truly” integrated sustainable solutions. However, our tools are still insufficient to perform the sustainable product-process synthesis integrally across the whole chemical supply chain. The ongoing development of concepts, methods and computer applications thus remains the most important role of the PSE community in order to provide engineers with powerful systems tools with which to shape sustainable development. The task, however, is very challenging even at the level of process synthesis since we are dealing with multi-criteria, an enormous amount of complex interactions, uncertainties, discrete and continuous decisions, giving rise to the use of the simultaneous, mixed-integer nonlinear programming (MINLP) approach. Although several efficient MINLP solvers have been developed in the last two decades, hardly any academic or professional MINLP synthesizer for solving such nontrivial synthesis problems has been developed so far. The present contribution wishes to shed light on some important issues relating to different challenges that had to and still have to be mastered as well as various capabilities which in turn were rewarded by mastering some of the challenges during the development of the advanced mixed-integer process synthesizer (MipSyn), the successor of the process synthesizer PROSYN-MINLP ( Kravanja & Grossmann, 1990, 1994). The primary aim of future research is oriented towards the development of an even more advanced and robust synthesizer shell, capable of solving large-scale sustainable applications in different engineering domains.

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