Details

<div>Lagrange Duality for Multi-Composed Optimization Problems.-&nbsp;Duality Results for Minmax Location Problems.-&nbsp;Solving Minmax Location Problems via Epigraphical Projection.-&nbsp;Numerical Experiments.</div>

<b>Dr. Oleg Wilfer</b> received his PhD at the Faculty of Mathematics of Chemnitz University of Technology, Germany. He is currently working as a development engineer in the automotive industry.

<div>Oleg Wilfer presents a new conjugate duality concept for geometric and cone constrained optimization problems whose objective functions are a composition of finitely many functions. As an application, the author derives results for single minmax location problems formulated by means of extended perturbed minimal time functions as well as for multi-facility minmax location problems defined by gauges. In addition, he provides formulae of projections onto the epigraphs of gauges to solve these kinds of location problems numerically by using parallel splitting algorithms. Numerical comparisons of recent methods show the excellent performance of the proposed solving technique.</div><div><br></div><div><b>Contents</b></div><div><ul><li>Lagrange Duality for Multi-Composed Optimization Problems</li><li>Duality Results for Minmax Location Problems</li><li>Solving Minmax Location Problems via Epigraphical Projection</li><li>Numerical Experiments</li></ul></div><div><b>Target Groups</b></div><div><ul><li>Scientists and students in the field of mathematics, applied mathematics and mathematical economics</li><li>Practitioners in these fields and mathematical optimization as well as operations research</li></ul></div><div><b>About the Author</b></div><div><b>Dr. Oleg Wilfer</b> received his PhD at the Faculty of Mathematics of Chemnitz University of Technology, Germany. He is currently working as a development engineer in the automotive industry.</div><div><br></div>

Presents a new conjugate duality concept