Convex underestimation strategies for signomial functions

Authors:
Andreas Lundell;Tapio Westerlund
Affiliations:
Process Design and Systems Engineering, Åbo Akademi University, Turku, Finland;Process Design and Systems Engineering, Åbo Akademi University, Turku, Finland
Venue:
Optimization Methods & Software - GLOBAL OPTIMIZATION
Year:
2009

Citing 3
Cited 3

Global optimization of mixed-integer nonlinear programs: A theoretical and computational study

Mathematical Programming: Series A and B
Some transformation techniques with applications in global optimization

Journal of Global Optimization
Global solution of optimization problems with signomial parts

Discrete Optimization

Global optimization

Optimization Methods & Software - GLOBAL OPTIMIZATION
An Efficient Global Approach for Posynomial Geometric Programming Problems

INFORMS Journal on Computing
A reformulation framework for global optimization

Journal of Global Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

Different types of underestimation strategies are used in deterministic global optimization. In this paper, convexification and underestimation techniques applicable to problems containing signomial functions are studied. Especially, power transformation and exponential transformation (ET) will be considered in greater detail and some new theoretical results regarding the relation between the negative power transformation and the ET are given. The techniques are, furthermore, illustrated through examples and compared with other underestimating methods used in global optimization solvers such as αBB and BARON.