most citedHospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic

10 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2021

Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis

Thomas Bartz-Beielstein, Marcel Dröscher, Alpar Gür +9

Crises like the COVID-19 pandemic pose a serious challenge to health-care institutions. They need to plan the resources required for handling the increased load, for instance, hosp…

stat.AP202010 cited

Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic

Thomas Bartz-Beielstein, Frederik Rehbach, Olaf Mersmann +1

We present a resource-planning tool for hospitals under special consideration of the COVID-19 pandemic, called babsim.hospital. It provides many advantages for crisis teams, e.g.,…

stat.AP20204 cited

Optimization of High-dimensional Simulation Models Using Synthetic Data

Thomas Bartz-Beielstein, Eva Bartz, Frederik Rehbach +1

Simulation models are valuable tools for resource usage estimation and capacity planning. In many situations, reliable data is not available. We introduce the BuB simulator, which…

cs.NE20206 cited

Continuous Optimization Benchmarks by Simulation

Martin Zaefferer, Frederik Rehbach

Benchmark experiments are required to test, compare, tune, and understand optimization algorithms. Ideally, benchmark problems closely reflect real-world problem behavior. Yet, rea…

cs.NE20201 cited

Expected Improvement versus Predicted Value in Surrogate-Based Optimization

Frederik Rehbach, Martin Zaefferer, Boris Naujoks +1

Surrogate-based optimization relies on so-called infill criteria (acquisition functions) to decide which point to evaluate next. When Kriging is used as the surrogate model of choi…