Skip to main content

A Framework for Globally Optimizing Mixed-Integer Signomial Programs

Author(s): Misener, Ruth; Floudas, Christodoulos A

To refer to this page use:
Abstract: Mixed-integer signomial optimization problems have broad applicability in engineering. Extending the Global Mixed-Integer Quadratic Optimizer, GloMIQO (Misener, Floudas in J. Glob. Optim., 2012. doi:10.1007/s10898-012-9874-7), this manuscript documents a computational framework for deterministically addressing mixed-integer signomial optimization problems to ε-global optimality. This framework generalizes the GloMIQO strategies of (1) reformulating user input, (2) detecting special mathematical structure, and (3) globally optimizing the mixed-integer nonconvex program. Novel contributions of this paper include: flattening an expression tree towards term-based data structures; introducing additional nonconvex terms to interlink expressions; integrating a dynamic implementation of the reformulation-linearization technique into the branch-and-cut tree; designing term-based underestimators that specialize relaxation strategies according to variable bounds in the current tree node. Computational results are presented along with comparison of the computational framework to several state-of-the-art solvers.
Publication Date: 2014
Citation: Misener, Ruth, and Christodoulos A. Floudas. "A Framework for Globally Optimizing Mixed-Integer Signomial Programs." Journal of Optimization Theory and Applications 161, no. 3 (2014): 905-932. doi: 10.1007/s10957-013-0396-3
DOI: doi:10.1007/s10957-013-0396-3
ISSN: 0022-3239
EISSN: 1573-2878
Pages: 905 - 932
Type of Material: Journal Article
Journal/Proceeding Title: Journal of Optimization Theory and Applications
Version: Author's manuscript

Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.