91 citations · 123 across the 7 of their papers we have counts for
7 papers
Transforming the Challenge of Constructing Low-Discrepancy Point Sets into a Permutation Selection Problem
François Clément, Carola Doerr, Kathrin Klamroth +1
Low discrepancy point sets have been widely used as a tool to approximate continuous objects by discrete ones in numerical processes, for example in numerical integration. Followin…
Ensuring connectedness for the Maximum Quasi-clique and Densest -subgraph problems
Daniela Scherer dos Santos, Kathrin Klamroth, Pedro Martins +1
Given an undirected graph , a quasi-clique is a subgraph of whose density is at least . Two optimization problems can be defined for quasi-cliques: the Ma…
On the online path extension problem -- Location and routing problems in board games
Konstantin Kraus, Kathrin Klamroth, Michael Stiglmayr
We consider an online version of a longest path problem in an undirected and planar graph that is motivated by a location and routing problem occurring in the board game "Turn & Ta…
Modeling Minimum Cost Network Flows With Port-Hamiltonian Systems
Onur Tanil Doganay, Kathrin Klamroth, Bruno Lang +2
We give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of clas…
Non-convex shape optimization by dissipative Hamiltonian flows
Matthias Bolten, Onur Tanil Doganay, Hanno Gottschalk +1
Shape optimization with constraints given by partial differential equations (PDE) is a highly developed field of optimization theory. The elegant adjoint formalism allows to comput…
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss
Fabian Heldmann, Sarah Berkhahn, Matthias Ehrhardt +1
Physics informed neural networks (PINNs) have proven to be an efficient tool to represent problems for which measured data are available and for which the dynamics in the data are…