Two men died after a Tesla vehicle that authorities believe was operating without anyone in the driver’s seat crashed into a tree Saturday night north of Houston. One of the men was in the front passenger’s seat and the other was in the back seat of the Tesla, which was traveling at high speed along a curve before it hit a tree around 11:25 p.m. local time, Harris County Precinct 4 Constable Mark Herman said in an interview. More: Wall Street Article https://www.wsj.com/articles/fatal-tesla-crash-in-texas-believed-to-be-driverless-11618766363
EvoStar2021 conference goes online and will be held from the 7th to the 9th of April of 2021. Our paper “Bayesian Networks for Mood Prediction Using Unobstrusive Ecological Momentary Assesments” (Margarita Alejandra Rebolledo Coy, A.E. Eiben and Thomas Bartz-Beielstein), see program overview, www.evostar.org/2021/programme/ that holds the links to all the sessions and https://easychair.org/smart-program/Evo2021/ for the Full Programme and details. The opening session and the keynotes will be live-streamed in the SPECIES YouTube Channel: www.youtube.com/c/SPECIESsociety
Authors: Thomas Bartz-Beielstein, Marcel Droescher, Alpar Guer, Alexander Hinterleitner, Tom Lawton, Olaf Mersmann, Dessislava Peeva, Lennard Reese, Frederik Rehbach, Nicolas Rehbach, Amrita Sen, Aleksandr Subbotin and Martin Zaefferer
Abstract: Hospitals and health-care institutions need to plan the resources required for handling the increased load, i.e., beds and ventilators during the COVID-19 pandemic. BaBSim.Hospital, an open-source tool for capacity planning based on discrete event simulation, was developed over the last year to support doctors, administrations, health authorities, and crisis teams in Germany. To obtain reliable results, 29 simulation parameters such as durations and probabilities must be specified. While reasonable default values were obtained in detailed discussions with medical professionals, the parameters have to be regularly and automatically optimized based on current data.
We aim to investigate how a set of parameters that is tailored to the German health system can be transferred to other regions. Therefore, we will use data from the UK. Our study demonstrates the flexibility of the discrete event simulation approach. However, transferring the optimal German parameter settings to the UK situation does not work—parameter ranges must be modified. The adaptation has been shown to reduce simulation errors by nearly 70%. The simulation-via-optimization approach is not restricted to health-care institutions, it is applicable to many other real-world problems, e.g., the development of new elevator systems to cover the last mile or simulation of student flow in academic study periods.
Highlights of the GECCO 2021 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: Easily Participate through our online platform, no installations required.
Fair Submission Assessment: Winners are determined automatically through our online portal, fully objectively, only based on the final result quality.
Publication Possibilities: We are able to accept 2-page submissions for the GECCO Companion; thus, publications are possible directly through competition participation.
Price money: The best solution will receive 300€, the second place 200€ and the third place 100€
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 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. The simulations will be executed through an interface and hosted on one of our servers (similar to our last year’s challenge).
Your goal is to find an optimal parameter configuration for the BaBSim.Hospital simulator with a very limited budget of objective function evaluations. The participants will be free to apply one or multiple optimization algorithms of their choice.
Like last year, we are able to provide the opportunity for all participants to submit 2-page algorithm descriptions for the GECCO Companion. Thus, it is now possible to create publications in a similar procedure to the Late-Breaking Abstracts (LBAs) directly through competition participation!
2-Page Algorithm Description Submission Deadline: 2021-04-12 23:59 To be held as part of the 2021 Genetic and Evolutionary Computation Conference (GECCO 2021) organized by ACM SIGEVO (https://gecco-2021.sigevo.org).