Abstract
In this paper we describe a method for obtaining sets of transformations for reformulating a mixed integer nonlinear programming (MINLP) problem containing nonconvex twice-differentiable (C-2) functions to a convex MINLP problem in an extended variable space. The method for obtaining the transformations is based on solving a mixed integer linear programming (MILP) problem given the structure of the nonconvex MINLP problem. The solution of the MILP problem renders a minimal set of transformations convexifying the nonconvex problem. This technique is implemented as an part of the alpha signomial global optimization algorithm (alpha SGO), a global optimization algorithm for nonconvex MINLP problems.
| Original language | Undefined/Unknown |
|---|---|
| Title of host publication | 11th International Symposium on Process Systems Engineering |
| Editors | Iftekhar A Karimi, Rajagopalan Srinivasan |
| Publisher | Elsevier |
| Pages | 1497–1501 |
| Number of pages | 5 |
| ISBN (Print) | 978-0-444-59505-8 |
| Publication status | Published - 2012 |
| MoE publication type | A4 Article in a conference publication |
| Event | conference - Duration: 1 Jan 2012 → … |
Conference
| Conference | conference |
|---|---|
| Period | 01/01/12 → … |
Keywords
- global optimization
- nonconvex MINLP problems
- reformulation techniques
- signomial functions