Publications
Since EvoAl is a research project, there are several academic publications related to EvoAl here. Perhaps, these papers answer some questions you have.
2024
Bernhard J. Berger, Christina Plump and Rolf Drechsler. EvoAl - Codeless Domain-Optimisation. In The Genetic and Evolutionary Computation Conference (GECCO Companion), 2024. accepted for publication
Christina Plump, Daniel C. Hoinkiss, Jörn Huber, Bernhard J. Berger, Matthias Günther, Christoph Lüth and Rolf Drechsler. Finding the perfect MRI sequence for your patient — Towards an optimisation workflow for MRI-sequences. In IEEE World Congress on Computational Intelligence (IEEE WCCI 2024), Yokohama, Japan, 2024. accepted for publication
2023
Christina Plump, Bernhard J. Berger and Rolf Drechsler. Repetitive Processes and Their Surrogate-Model Congruent Encoding for Evolutionary Algorithms - A Theoretic Proposal. The Genetic and Evolutionary Computation Conference (GECCO Companion), 2023. DOI
Bernhard J. Berger, Christina Plump and Rolf Drechsler. EvoAl: A domain-specific language-based approach to optimisation. In 2023 IEEE Congress on Evolutionary Computation (CEC), 2023. DOI
Christina Plump, Rolf Drechsler, Bernhard J. Berger. KI-gestützte Optimierung repetitiver Prozesse - Eine Kodierungstechnik für repetitive Prozesse in der evolutionären Optimierung. Industrie 4.0 Management, 2023. DOI
2022
Christina Plump, Bernhard J. Berger and Rolf Drechsler. Using density of training data to improve evolutionary algorithms with approximative fitness functions. In 2022 IEEE Congress on Evolutionary Computation (CEC), 2022. DOI
Christina Plump, Bernhard J. Berger and Rolf Drechsler. Adapting mutation and recombination operators to range-aware relations in real-world application data. In The Genetic and Evolutionary Computation Conference (GECCO Companion), 2022. DOI
Christina Plump, Bernhard J. Berger and Rolf Drechsler. Choosing the right technique for the right restriction - a domain-specific approach for enforcing search-space restrictions in evolutionary algorithms. In Proceedings of the 8th International Conference on Dynamics in Logistics – LDIC 2022, 2022. DOI
2021
Christina Plump, Bernhard J. Berger, Rolf Drechsler. Improving Evolutionary Algorithms by Enhancing an Approximative Fitness Function Through Prediction Intervals. In 2021 IEEE Congress on Evolutionary Computation (CEC), 2021. DOI
Christina Plump, Bernhard J. Berger, Rolf Drechsler. Domain-driven Correlation-aware Recombination and Mutation Operators for Complex Real-world Applications. In 2021 IEEE Congress on Evolutionary Computation (CEC), 2021. DOI