Convexification techniques for signomial functions in mixed-integer nonlinear optimization
The topic of this presentation is how to utilize so-called lifting exponential and power transformations in combination with linearization techniques to solve nonconvex mixed integer nonlinear optimization (also called mixed-integer nonlinear programming – MINLP) problems containing signomial functions. Signomial functions are sums of terms, where each term is a product of power functions. This function class is quite general and contain common nonconvexities in optimization problems such as bilinear and trilinear terms.
Time: Fri 2022-11-25 11.00 - 12.00
Video link: Zoom room 63658381373
Lecturer: Andreas Lundell
Senior University Lecturer
Department of Information Technology
Åbo Akademi University, Vaasa, Finland