Convexification techniques for signomial functions in mixed-integer nonlinear optimization

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Beskrivning

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.
Period25 nov. 2022
VidKTH Royal Institute of Technology, Sverige
OmfattningInternationell