Kathrin Klamroth

Professor for Mathematical Optimization

Bergische Universität Wuppertal

Germany

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Professor Kathrin Klamroth is a faculty member at Bergische Universität Wuppertal, Germany. Her research primarily focuses on mathematical optimization, with recent publications covering topics such as multiobjective optimization, shape optimization, and decision-making support in high-dimensional outcome environments. She has contributed significantly to the field through her work on algorithms for multiobjective integer programming and the modeling of network flows.

Articles (20)

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2025

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2024

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2024

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2021

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2021

Collaborators (10)

Claudia Totzeck

Bergische Universität Wuppertal

GERMANY

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Kaisa Miettinen

Professor

University of Jyväskylä

FINLAND

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Michael Stiglmayr

Bergische Universität Wuppertal

GERMANY

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Julia Sudhoff

Bergische Universität Wuppertal

GERMANY

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Bhupinder Singh Saini

University of Jyväskylä

FINLAND

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Arne Schulz

Universität Hamburg

GERMANY

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Lars Relund Nielsen

Aarhus University

DENMARK

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Sune Lauth Gadegaard

Aarhus University

DENMARK

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Matthias Ehrhardt

Full Professor

Bergische Universität Wuppertal

GERMANY

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Luís Paquete

Associate Professor

University of Coimbra

PORTUGAL

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Kathrin Klamroth

Research Interests

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Articles (20)

Solving the Multiobjective Quasi-clique Problem

Consensus-based optimization for multi-objective problems: a multi-swarm approach

A tight formulation for the dial-a-ride problem

Efficient dominance filtering for unions and Minkowski sums of non-dominated sets

SCORE Band Visualizations: Supporting Decision Makers in Comparing High-Dimensional Outcome Vectors in Multiobjective Optimization

A simple, efficient and versatile objective space algorithm for multiobjective integer programming

Non-convex shape optimization by dissipative Hamiltonian flows

PINN training using biobjective optimization: The trade-off between data loss and residual loss

Ordinal optimization through multi-objective reformulation

Modeling Minimum Cost Network Flows With Port‐Hamiltonian Systems

Branch-and-bound and objective branching with three or more objectives

Event-based MILP models for ridepooling applications

Exact algorithms for multiobjective linear optimization problems with integer variables: A state of the art survey

Multi-objective matroid optimization with ordinal weights

Efficient and sparse neural networks by pruning weights in a multiobjective learning approach

Biobjective optimization problems on matroids with binary costs

Decision space robustness for multi-objective integer linear programming

A local analysis to determine all optimal solutions of k-max location problems on networks

Hypervolume scalarization for shape optimization to improve reliability and cost of ceramic components

Nonconvex constrained optimization by a filtering branch and bound

Collaborators (10)

Claudia Totzeck

Kaisa Miettinen

Michael Stiglmayr

Julia Sudhoff

Bhupinder Singh Saini

Arne Schulz

Lars Relund Nielsen

Sune Lauth Gadegaard

Matthias Ehrhardt

Luís Paquete

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