Peter Kirst is a scientist working on different optimization problems at the Operations Research and Logisitics group at Wageningen University & Research. He is interested in computing globally as well as good locally optimal points in various applications of interest in logistics, in particular inventory problems. Moreover, he is interested in data science and machine learning, especially for the improvement of supply chains.
He graduated from Karlsruhe Institute of Technology (KIT) in Germany where he worked on (standard) nonlinear problems as well as even more challenging types of problems such as semi-infinite programs and (generalized) disjunctive programs. In order to solve these problems to global optimality he developed several branch-and-bound methods tailored to the specific problem at hand. Also for this line of research the motivation always came from applications, notably from timber industry. In addition, several questions in machine learning such as cluster analysis or spline approximations give rise to interesting optimization problems in that area.