Reproducibility in optimization, machine learning, and artificial intelligence is an important issue. Today, on 2023-04-13, the paper
Ege de Bruin, Sarah L. Thomson, and Daan van den Berg. Frequency Fitness Assignment on JSSP: A Critical Review. In Proceedings of the 26th European Conference on Applications of Evolutionary Computation (EvoApplications'23), Held as Part of EvoStar'23, April 12-14, 2023, Brno, Czech Republic, pages 351-363. ISBN: 978-3-031-30228-2. Cham, Switzerland: Springer. doi:10.1007/978-3-031-30229-9_23
was presented by Mr. Ege de Bruin at the EvoStar 2023 conference in Brno, Czech Republic. In this work, de Bruin, von den Berg, and Thomson independently reproduce our experiments from the paper
Thomas Weise, Xinlu Li, Yan Chen, and Zhize Wu. Solving Job Shop Scheduling Problems Without Using a Bias for Good Solutions. In Genetic and Evolutionary Computation Conference Companion (GECCO'21 Companion), July 10-14, 2021, Lille, France. ACM, New York, NY, USA. ISBN 978-1-4503-8351-6. doi:10.1145/3449726.3463124 / slides / video presentation
They confirm our findings with high precision. Learning about the efforts made us very happy, as it not just shows that our work on Frequency Fitness Assignment (recently presented here and here) is interesting for others, but also that our results can be reproduced by re-implementing our algorithms using a different programming language on a different hardware platform. We deeply and sincerely thank the authors of going through this effort.
Mr. Ege de Bruin presenting the paper 'Frequency Fitness Assignment on JSSP: A Critical Review' at EvoStar'2023.