Andreas Lundell: 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.