Convex underestimation strategies for signomial functions
Optimization Methods & Software - GLOBAL OPTIMIZATION
A review of recent advances in global optimization
Journal of Global Optimization
Exponential and power transformations for convexifying signomial terms in MINLP problems
MIC '08 Proceedings of the 27th IASTED International Conference on Modelling, Identification and Control
An Efficient Global Approach for Posynomial Geometric Programming Problems
INFORMS Journal on Computing
A reformulation framework for global optimization
Journal of Global Optimization
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In this paper some transformation techniques, based on power transformations, are discussed. The techniques can be applied to solve optimization problems including signomial functions to global optimality. Signomial terms can always be convexified and underestimated using power transformations on the individual variables in the terms. However, often not all variables need to be transformed. A method for minimizing the number of original variables involved in the transformations is, therefore, presented. In order to illustrate how the given method can be integrated into the transformation framework, some mixed integer optimization problems including signomial functions are finally solved to global optimality using the given techniques.