From the 1 of 5 linked papers with an AI index.
5 papers
A Solution Concept for Convex Vector Optimization Problems based on a User-defined Region of Interest
Daniel Dörfler, Rebecca Köhler, Andreas Löhne
The paper proposes a new solution concept for arbitrary convex vector optimization problems that uses homogenization of the upper image and relative error measures, avoiding extra…
Low-Rank Multi-Objective Linear Programming
Andreas Löhne, Pascal Zillmann
When solving multi-objective programs (MOLPs), the number of objectives essentially determines the computing time. This can even lead to practically unsolvable problems. Consequent…
Multi-objective stochastic linear programming with recourse and flexible decision making
Andreas H. Hamel, Andreas Löhne
Optimal inventory leads to stochastic optimization problems where deterministic delivery decisions have to be made in advance of stochastic demand realizations. Similarly, risk dep…
MOCVXPY: a CVXPY extension for multiobjective optimization
Ludovic Salomon, Daniel Dörfler, Andreas Löhne
MOCVXPY is an open-source Python library for convex vector optimization. It is built on top of CVXPY, a domain-specific language for single-objective convex optimization. MOCVXPY e…
Computing all Nash equilibria of low-rank bi-matrix games
Zachary Feinstein, Andreas Löhne, Birgit Rudloff
We study constrained bi-matrix games, with a particular focus on low-rank games. Our main contribution is a framework that reduces low-rank games to smaller, equivalent constrained…