GECCO Challenge 2022: Industrial Challenge: Call for Participation

gecco 2022 gecco (Bild: ACM)


July 9-13, hybrid
Sponsored by ACM SIGEVO
Largest Conference in the Field of Genetic and Evolutionary Computation


Simulation models are valuable tools for resource usage estimation and capacity planning. The simulator, BaBSim.Hospital, explicitly covers difficulties for hospitals caused by the COVID-19 pandemic. The simulator can handle many aspects of resource planning in hospitals, such as intensive care unit (ICU) beds, ventilators or personal, while taking into consideration several cohorts as age or current health status.

The task represents an instance of an expensive, high-dimensional computer simulation-based optimization problem. Your goal is to find an optimal parameter configuration for the BaBSim.Hospital. The participants will be free to apply one or multiple optimization algorithms of their choice.

Highlights of the GECCO 2022 Industrial Challenge include:

  • Interesting Problem Domain: The impact of COVID-19 on the health system is ongoing and tools to help in capacity planning are more important than ever
  • Real-world Problems: Test your algorithms and methods, directly on real and current data.
  • Easy Access: Easy to participate with simple setup
  • Fair Submission Assessment: Winners are determined automatically through our online portal, fully objectively, only based on the final result quality

About the Optimization Problem

The BaBSim.Hospital simulates the typical course of treatment of COVID 19 patients on the basis of user set scenarios, such as a specific reproduction number. With these scenarios "BaBSim.Hospital" can calculate the demand for hospital beds. The transition probabilities between hospital stations and the lengths of stay of Covid 19 patients required for the simulation were statistically validated by medical professionals and using about half a million data. This allows BaBSim.Hospital to be a useful tool for depiction and evaluation of different pandemic development scenarios.


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