Extra Material

Supplementary material

  • Afsar, B., Silvennoinen, J., Misitano, G., Ruiz, F., Ruiz, A.B., Miettinen, K., Designing Empirical Experiments to Compare Interactive Multiobjective Optimization Methods, manuscript. Supplementary material in NextCloud (Sustainability problem and interactive methods compared); Supplementary material in NextCloud (Summary of the sustainability problem)
  • Afsar B., Miettinen, K., and Ruiz, A.B., Artificial Decision Maker for Comparing Reference Point Based Interactive Evolutionary Multiobjective Optimization Methods, in "11th International Conference Series on Evolutionary Multi-Criterion Optimization (EMO 2021), Proceedings", Edited by H. Ishibuchi, Q. Zhang, R. Cheng, K. Li, H. Li, H. Wang, A. Zhou, Springer, 619-631, 2021. Supplementary material on github. Code
  • Lovison, A., Miettinen, K., On the Extension of the DIRECT Algorithm to Multiple Objectives, Journal of Global Optimization, 79(2), 387-412, 2021. Supplementary material in GeoGebra
  • Mazumdar, A., Chugh, T., Hakanen, J., Miettinen, K., An Interactive Framework for Offline Data-Driven Multiobjective Optimization, in "9th International Conference on Bioinspired Optimisation Methods and Their Applications (BIOMA 2020), Proceedigs", Edited by B Filipic, E. Minisci, M. Vasile, Springer, 97-209, 2020. Supplementary material on github,
  • Habib, A., Singh, H.K., Chugh, T., Ray, T. Miettinen, K., A Multiple Surrogate Assisted Decomposition-Based Evolutionary Algorithm for Expensive Multi/Many-Objective Optimization, IEEE Transactions on Evolutionary Computation, 23(6), 1000-1014, 2019. Supplementary material
  • Mazumdar, A., Chugh, T., Miettinen, K., Lopez-Ibanez, M. On Dealing with Uncertainties from Kriging Models in Offline Data-driven Evolutionary Multiobjective Optimization, in "10th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2019), Proceedings", Edited by K. Deb, E. Goodman, C. A. C. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed, Springer, 463-474, 2019. Supplementary material on github
  • Fieldsend, J.E., Chugh, T., Allmendinger, R., Miettinen, K., A Feature Rich Distance-Based Many-Objective Visualisable Test Problem Generator, in "Proceedings of the Genetic and Evolutionary Computation Conference, (GECCO-2019), Edited by M. Lopez-Ibanez, The Association of Computing Machinery (ACM), New York, 541-549, 2019. Generator code in github
  • Chugh, T., Allmendinger, R., Ojalehto, V., Miettinen, K., A surrogate-assisted EMOA for problems with non-uniform objective latencies, in " Proceedings of the 23rd Genetic and Evolutionary Computation Conference (GECCO-2018)", Edited by H. Aguirre, The Association of Computing Machinery (ACM), 609-616, 2018. Supplementary material on github