Computational studies using a novel simplicial-approximation based algorithm for MINLP optimization

Significant advances have been made in the last two decades for the effective solution of mixed integer non-linear programming (MINLP) problems, mainly by exploiting the special structure of the problem that results under certain convexity assumptions. This paper discusses the computational experience with a novel decomposition algorithm which is based on the idea of closely approximating the feasible region defined by the set of constraints by a convex polytope using the simplicial approximation approach (Goyal and Ierapetritou, 2003b). A variety of problems are solved including structural flowsheet optimization, design of batch processes and trim-loss minimization to illustrate the applicability and efficiency of the proposed approach. © 2004 Published by Elsevier Ltd.