MCDM 2026 in Wuppertal: Results from the cooperation with Everllence
MCDM 2026 in Wuppertal: Bartz-Beielstein presents results from the Everllence cooperation
2026-06-18
At MCDM 2026, the 28th International Conference on Multiple Criteria Decision Making (25–29 May 2026 at the University of Wuppertal), Prof. Dr. Thomas Bartz-Beielstein presented results from a long-standing cooperation with Everllence SE (formerly MAN Energy Solutions, Augsburg). His talk on 28 May was part of the session Bayesian and Surrogate-Model Assisted Multiobjective Optimization (stream Heuristic Algorithms), chaired by Michael Emmerich.
The talk centred on the approach Multi-Objective Optimization with Desirability and Morris-Mitchell Criterion, developed jointly with Everllence and Bartz & Bartz GmbH. The corresponding paper is now available on arXiv, and the abstract was accepted for presentation at MCDM 2026. Background and methodology are described in detail in the acceptance announcement: the method combines desirability functions with the Morris-Mitchell criterion to merge surrogate-model predictions and the space-filling quality of existing experimental designs into a single score. The implementation builds on the open-source Python packages spotdesirability and spotoptim and is demonstrated on a compressor-development case study.
The close link between methodological research and industrial application drew strong interest from the MCDM community. Prof. Bartz-Beielstein received valuable feedback and held stimulating discussions with leading researchers in multi-objective optimization. The exchange directly supports both the further development of the methods and the cooperation with Everllence.
Paper: Bartz-Beielstein, T., Bartz, E., Hinterleitner, A., Leitenmeier, C., Abd El Hussein, I. (2026). Multi-Objective Optimization with Desirability and Morris-Mitchell Criterion. arXiv:2512.21989.