Christina Büsing
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Perfect Matching Under Precedence Constraints Open
In this article, we motivate and define variants of perfect matching under precedence constraints where a perfect matching is built incrementally and precedence constraints ensure that an edge may only be added to the matching if the edge'…
Minimum‐Peak‐Cost Flows Over Time Open
Peak cost is a novel objective for flows over time that describes the amount of workforce necessary to run a system. We focus on minimizing peak costs in the context of maximum temporally repeated flows and formulate the corresponding MPC‐…
View article: Generating realistic patient data
Generating realistic patient data Open
Developing algorithms for real-life problems that perform well in practice highly depends on the availability of realistic data for testing. Obtaining real-life data for optimization problems in health care, however, is often difficult. Th…
Precedence‐Constrained Shortest Path Open
We propose a variant of the shortest path problem where the order in which vertices occur in the path is subject to precedence constraints. Precedence constraints are defined in terms of vertex pairs which indicate that a vertex is the pre…
A Faster Parametric Search for the Integral Quickest Transshipment Problem Open
Algorithms for computing fractional solutions to the quickest transshipment problem have been significantly improved since Hoppe and Tardos first solved the problem in strongly polynomial time. For integral solutions, runtime improvements …
Robust Capacity Expansion Modelling for Renewable Energy Systems Open
Future greenhouse gas neutral energy systems will be dominated by renewable energy technologies whose energy output and utilisation is subject to uncertain weather conditions. This work proposes an algorithm for capacity expansion planning…
Combinatorial and Computational Insights about Patient-to-room Assignment under Consideration of Roommate Compatibility Open
During a hospital stay, a roommate can significantly influence a patient's overall experience both positivly and negatively. Therefore, hospital staff tries to assign patients together to a room that are likely to be compatible. However, t…
Recycling valid inequalities for robust combinatorial optimization with budgeted uncertainty Open
Robust combinatorial optimization with budgeted uncertainty is one of the most popular approaches for integrating uncertainty into optimization problems. The existence of a compact reformulation for (mixed-integer) linear programs and posi…
Structural Insights and an IP-based Solution Method for Patient-to-room Assignment under Consideration of Single Room Entitlements Open
Patient-to-room assignment (PRA) is a scheduling problem in decision support for hospitals. It consists of assigning patients to rooms according to certain objectives, e.g., avoiding transfers and respecting single-room requests. This work…
The complexity of the timetable‐based railway network design problem Open
Because of the long planning periods and their long life cycle, railway infrastructure has to be outlined long ahead. At the present, the infrastructure is designed while only little about the intended operation is known. Hence, the timeta…
Robust transshipment problem under consistent flow constraints Open
In this article, we study robust transshipment under consistent flow constraints. We consider demand uncertainty represented by a finite set of scenarios and characterize a subset of arcs as so‐called fixed arcs. In each scenario, we requi…
A branch and bound algorithm for robust binary optimization with budget uncertainty Open
Since its introduction in the early 2000s, robust optimization with budget uncertainty has received a lot of attention. This is due to the intuitive construction of the uncertainty sets and the existence of a compact robust reformulation f…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function. The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the ro…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function. The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the ro…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function. The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the ro…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization under budget uncertainty that have been described and used for benchmarking in the paper "A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty", p…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function. The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the ro…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide a set of instances for robust combinatorial optimization under budget uncertainty that have been described and used for benchmarking in the paper "A Branch & Bound Algorithm for Robust Binary Optimization with Budget Uncertainty…
Benchmark Instances for Robust Combinatorial Optimization with Budgeted Uncertainty Open
We provide test instances for robust combinatorial optimization with budget uncertainty in the objective function. The set contains nominal problems from the MIPLIB 2017 that have been converted into robust problems and instances of the ro…
Robust transshipment problem under consistent flow constraints Open
In this paper, we study robust transshipment under consistent flow constraints. We consider demand uncertainty represented by a finite set of scenarios and characterize a subset of arcs as so-called fixed arcs. In each scenario, we require…
Interacting brains revisited: A cross‐brain network neuroscience perspective Open
Elucidating the neural basis of social behavior is a long‐standing challenge in neuroscience. Such endeavors are driven by attempts to extend the isolated perspective on the human brain by considering interacting persons' brain activities,…
Robust minimum cost flow problem under consistent flow constraints Open
The robust minimum cost flow problem under consistent flow constraints (RobMCF $$\equiv $$ ) is a new extension of the minimum cost flow (MCF) problem. In the RobMCF $$\equiv $$ problem, we consider demand and supply that are subject to un…
The Dial-a-Ride Problem in Primary Care with Flexible Scheduling Open
Patient transportation systems are instrumental in lowering access barriers in primary care by taking patients to their GPs. As part of this setting, each transportation request of a chronic or walk-in patient consists of an outbound trip …
Preface: Special issue on network analytics and optimization Open
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