Publications
PhD thesesBao Quoc Ta: "Excessive functions, Appell polynomials and optimal stopping"
May 08, 2014 Andreas Lundell PhD theses
The main topic of the thesis is optimal stopping. This is treated in two research articles. In the first article we introduce a new approach to optimal stopping of general strong Markov processes. The approach is based on the representation of excessive functions as expected suprema. We present a variety of examples, in particular, the Novikov-Shiryaev problem for Lévy processes. In the second article on optimal stopping we focus on differentiability of excessive functions of diffusions and apply these results to study the validity of the principle of smooth fit.
Read moreAnders Skjäl: "On the Use of Convex Underestimators in Global Optimization"
April 10, 2014 Andreas Lundell PhD theses
My thesis gives a broad introduction to nonconvex mathematical programming and the use of convex underestimators. Complexity theory provides valuable perspectives on the hardness of optimization. I review basic concepts from complexity theory in one chapter, especially ideas pertaining to optimization and approximation.
Read moreAxel Nyberg: "Some Reformulations for the Quadratic Assignment Problem"
March 28, 2014 Andreas Lundell PhD theses
The quadratic assignment problem (QAP) is often referred to as a facility location problem where the goal is to determine the best placing of facilities on a predefined set of locations.
Read morePeter Lindberg: "The knapsack problem approach in solving partial hedging problems of options"
August 31, 2012 Andreas Lundell PhD theses
This thesis introduces a new approach for studying the problem of optimal partial hedging of both European and American options in a finite and complete discrete-time market model.
Read moreToni Lastusilta: "GAMS MINLP Solver Comparisons and Some Improvements to the AlphaECP Algorithm"
December 02, 2011 Andreas Lundell PhD theses
This PhD thesis studies the solving capability of some solvers for optimization problems, as well as presenting some improvements to one of the solvers.
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