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.

• Type: Journal
• Year: 2004
• Where: CCE
• Authors: Vishal Goyal, Marianthi G. Ierapetritou
• Keywords: CCE 2004, CCE 2007, Certain Convexity Assumptions, Integer Non-linear Programming, Simplicial Approximation Approach