| Evaluation of multi-objective optimization approaches for solving green supply chain design problems M Kadziński, T Tervonen, MK Tomczyk, R Dekker Omega 68, 168-184, 2017 | 83 | 2017 |
| Decomposition-based interactive evolutionary algorithm for multiple objective optimization MK Tomczyk, M Kadziński IEEE Transactions on Evolutionary Computation 24 (2), 320-334, 2019 | 47 | 2019 |
| Preference-based cone contraction algorithms for interactive evolutionary multiple objective optimization M Kadziński, MK Tomczyk, R Słowiński Swarm and Evolutionary Computation 52, 100602, 2020 | 29 | 2020 |
| Interactive evolutionary multiple objective optimization for group decision incorporating value-based preference disaggregation methods M Kadziński, MK Tomczyk Group Decision and Negotiation 26, 693-728, 2017 | 23 | 2017 |
| EMOSOR: Evolutionary multiple objective optimization guided by interactive stochastic ordinal regression MK Tomczyk, M Kadziński Computers & operations research 108, 134-154, 2019 | 18 | 2019 |
| Decomposition-based co-evolutionary algorithm for interactive multiple objective optimization MK Tomczyk, M Kadziński Information Sciences 549, 178-199, 2021 | 16 | 2021 |
| On the elicitation of indirect preferences in interactive evolutionary multiple objective optimization MK Tomczyk, M Kadziński Proceedings of the 2020 genetic and evolutionary computation conference, 569-577, 2020 | 11 | 2020 |
| Robust indicator-based algorithm for interactive evolutionary multiple objective optimization MK Tomczyk, M Kadziński Proceedings of the Genetic and Evolutionary Computation Conference, 629-637, 2019 | 11 | 2019 |
| Interactive co-evolutionary multiple objective optimization algorithms for finding consensus solutions for a group of Decision Makers MK Tomczyk, M Kadziński Information Sciences 616, 157-181, 2022 | 5 | 2022 |
| Interactive Cone Contraction for Evolutionary Mutliple Objective Optimization M Kadziński, MK Tomczyk, R Słowiński Advances in Data Analysis with Computational Intelligence Methods: Dedicated …, 2018 | 2 | 2018 |
| Co-evolution improves the efficiency of preference learning methods when the Decision Maker's aspirations develop over time M Tomczyk, M Kadziński Proceedings of the Genetic and Evolutionary Computation Conference, 759-767, 2023 | 1 | 2023 |
| Interactive evolutionary multiple objective optimization algorithm using a fast calculation of holistic acceptabilities MK Tomczyk, M Kadziński Proceedings of the Genetic and Evolutionary Computation Conference, 476-484, 2021 | 1 | 2021 |
| Using ordinal regression for interactive evolutionary multiple objective optimization with multiple decision makers M Kadziński, M Tomczyk Outlooks and Insights on Group Decision and Negotiation: 15th International …, 2015 | 1 | 2015 |
| Evolutionary algorithms for solving single-and multiple-objective political redistricting problems: The case study of Poland MK Tomczyk, M Kadziński Applied Soft Computing 152, 111258, 2024 | | 2024 |
Miłosz KadzińskiPoznan University of Technology, Faculty of Computing and Telecommunications, Institute of ComputingVerified email at cs.put.poznan.pl
