12 citations · 19 across the 18 of their papers we have counts for
19 papers
Representing the Non-dominated Set of Multi-objective Optimization Problems with Polyhedral Ordering Cones
Chiara Weuste, Michael Stiglmayr
In the literature, research on representing the non-dominated set has focused almost exclusively on multi-objective optimization problems with Pareto-dominance. However, general or…
Consistent Path Selection for Bi-objective Median Location Problems on Graphs
Renée Lamsfuß, Kathrin Klamroth, Michael Stiglmayr +1
We consider single-facility median location problems on graphs where two conflicting cost values are associated with the edges. As an example, suppose that a decision maker wants t…
Adapting Polyhedral Dominance Cones to Ordinal Preference Structures
Kathrin Klamroth, Michael Stiglmayr, Julia Sudhoff Santos
In combinatorial optimization, ordinal costs can be used to model the quality of elements whenever numerical values are not available. When considering, for example, routing proble…
On the Computational Complexity of Multi-Objective Ordinal Unconstrained Combinatorial Optimization
José Rui Figueira, Kathrin Klamroth, Michael Stiglmayr +1
Multi-objective unconstrained combinatorial optimization problems (MUCO) are in general hard to solve, i.e., the corresponding decision problem is NP-hard and the outcome set is in…
The Line-Based Dial-a-Ride Problem
Kendra Reiter, Marie Schmidt, Michael Stiglmayr
On-demand ridepooling systems offer flexible services pooling multiple passengers into one vehicle, complementing traditional bus services. We propose a transportation system combi…
A Tight Formulation for the Dial-a-Ride Problem
Daniela Gaul, Kathrin Klamroth, Christian Pfeiffer +2
Ridepooling services play an increasingly important role in modern transportation systems. With soaring demand and growing fleet sizes, the underlying route planning problems becom…
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…
A new perspective on dynamic network flow problems via port-Hamiltonian systems
Onur Tanil Doganay, Kathrin Klamroth, Bruno Lang +2
We suggest a global perspective on dynamic network flow problems that takes advantage of the similarities to port-Hamiltonian dynamics. Dynamic minimum cost flow problems are formu…
Ridepooling and public bus services: A comparative case-study
Hayk Asatryan, Daniela Gaul, Hanno Gottschalk +2
This case-study aims at a comparison of the service quality of time-tabled buses as compared to on-demand ridepooling cabs in the late evening hours in the city of Wuppertal, Germa…
Consensus-Based Optimization for Multi-Objective Problems: A Multi-Swarm Approach
Kathrin Klamroth, Michael Stiglmayr, Claudia Totzeck
We propose a multi-swarm approach to approximate the Pareto front of general multi-objective optimization problems that is based on the Consensus-based Optimization method (CBO). T…
Determining Cost-Efficient Controls of Electrical Energy Storages Using Dynamic Programming
Michael Stiglmayr, Svenja Uhlemeyer, Björn Uhlemeyer +1
Volatile electrical energy prices are a challenge and an opportunity for small and medium-size companies in energy-intensive industries. By using electrical energy storage and/or a…
Ordinal Optimization Through Multi-objective Reformulation
Kathrin Klamroth, Michael Stiglmayr, Julia Sudhoff
We analyze combinatorial optimization problems with ordinal, i.e., non-additive, objective functions that assign categories (like good, medium and bad) rather than cost coefficient…
Multi-objective Matroid Optimization with Ordinal Weights
Kathrin Klamroth, Michael Stiglmayr, Julia Sudhoff
Bi-objective optimization problems on matroids are in general intractable and their corresponding decision problems are in general NP-hard. However, if one of the objective functio…
Event-based MILP models for ride pooling applications
Daniela Gaul, Kathrin Klamroth, Michael Stiglmayr
Ridepooling services require efficient optimization algorithms to simultaneously plan routes and pool users in shared rides. We consider a static dial-a-ride problem (DARP) where a…
Efficient and Sparse Neural Networks by Pruning Weights in a Multiobjective Learning Approach
Malena Reiners, Kathrin Klamroth, Michael Stiglmayr
Overparameterization and overfitting are common concerns when designing and training deep neural networks, that are often counteracted by pruning and regularization strategies. How…
GivEn -- Shape Optimization for Gas Turbines in Volatile Energy Networks
Jan Backhaus, Matthias Bolten, Onur Tanil Doganay +19
This paper describes the project GivEn that develops a novel multicriteria optimization process for gas turbine blades and vanes using modern "adjoint" shape optimization algorithm…
Gradient Based Biobjective Shape Optimization to Improve Reliability and Cost of Ceramic Components
Onur T. Doganay, Hanno Gottschalk, Camilla Hahn +3
We consider the simultaneous optimization of the reliability and the cost of a ceramic component in a biobjective PDE constrained shape optimization problem. A probabilistic Weibul…
Introducing Multiobjective Complex Systems
Tobias Dietz, Kathrin Klamroth, Konstantin Kraus +5
This article focuses on the optimization of a complex system which is composed of several subsystems. On the one hand, these subsystems are subject to multiple objectives, local co…