| 2026 | GECCO | Limited Perfect Monotonical Surrogates Constructed Using Low-Cost Recursive Linkage Discovery with Guaranteed Output. | Michal Witold Przewozniczek, Francisco Chicano, Marcin Komarnicki, Renato Tins |
| 2026 | GECCO | The hop-like problem nature - unveiling and modelling new features of real-world problems. | Michal Witold Przewozniczek, Bartosz Frej, Marcin Komarnicki |
| 2025 | FOGA | Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-Based Function Concatenations. | Michal Prusik, Bartosz Frej, Michal Witold Przewozniczek |
| 2025 | FOGA | Conditional Direct Empirical Linkage Discovery for Solving Multi-Structured Problems. | Michal Witold Przewozniczek, Peter A. N. Bosman, Anton Bouter, Arthur Guijt, Marcin M. Komarnicki, Dirk Thierens |
| 2025 | FOGA | Empirical Linkage Discovery in Bi-Objective Optimization. | Michal Witold Przewozniczek, Marcin M. Komarnicki, Renato Tins |
| 2025 | GECCO | Moving between high-quality optima using multi-satisfiability characteristics in hard-to-solve Max3Sat instances. | Jedrzej Piatek, Michal Witold Przewozniczek, Francisco Chicano, Renato Tins |
| 2025 | GECCO | On Revealing the Hidden Problem Structure in Real-World and Theoretical Problems Using Walsh Coefficient Influence. | Michal Witold Przewozniczek, Francisco Chicano, Renato Tins, Jakub Nalepa, Bogdan Ruszczak, Agata Wijata |
| 2025 | GECCO | On Defining and Discovering Non-Symmetrical Dependencies. | Michal Witold Przewozniczek, Bartosz Frej, Marcin M. Komarnicki |
| 2025 | GECCO | Subfunction Structure Matters: A New Perspective on Local Optima Networks. | Sarah L. Thomson, Michal Witold Przewozniczek |
| 2025 | GECCO | Genetic Feature Selection for Multimodal Wound Detection. | Agata M. Wijata, Maria J. Bienkowska, Michal Witold Przewozniczek, Jakub Nalepa |
| 2025 | GECCO | Machine Learning and Genetic Algorithms: An Intricate Relationship for Locating Methane in Satellite Images. | Agata M. Wijata, Nicolas Longp, Michal Witold Przewozniczek, Jakub Nalepa |
| 2024 | GECCO | Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems. | Marcin Michal Komarnicki, Michal Witold Przewozniczek, Renato Tins, Xiaodong Li |
| 2023 | GECCO | Incremental Recursive Ranking Grouping - A Decomposition Strategy for Additively and Nonadditively Separable Problems. | Marcin Michal Komarnicki, Michal Witold Przewozniczek, Halina Kwasnicka, Krzysztof Walkowiak |
| 2023 | GECCO | To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary computation. | Michal Witold Przewozniczek, Marcin Michal Komarnicki |
| 2023 | GECCO | First Improvement Hill Climber with Linkage Learning - on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms. | Michal Witold Przewozniczek, Renato Tins, Marcin Michal Komarnicki |
| 2022 | GECCO | Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem. | Michal Witold Przewozniczek, Marcin M. Komarnicki |
| 2022 | GECCO | On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. | Michal Witold Przewozniczek, Renato Tins, Bartosz Frej, Marcin M. Komarnicki |
| 2022 | GECCO | Iterated local search with perturbation based on variables interaction for pseudo-boolean optimization. | Renato Tins, Michal Witold Przewozniczek, Darrell Whitley |
| 2021 | CEC | Fitness Caching - From a Minor Mechanism to Major Consequences in Modern Evolutionary Computation. | Michal Witold Przewozniczek, Marcin M. Komarnicki |
| 2021 | GECCO | Multi-objective parameter-less population pyramid in solving the real-world and theoretical problems. | Michal Witold Przewozniczek, Piotr Dziurzanski, Shuai Zhao, Leandro Soares Indrusiak |
| 2021 | GECCO | Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. | Michal Witold Przewozniczek, Marcin M. Komarnicki, Peter A. N. Bosman, Dirk Thierens, Bartosz Frej, Ngoc Hoang Luong |
| 2021 | GECCO | Direct linkage discovery with empirical linkage learning. | Michal Witold Przewozniczek, Marcin Michal Komarnicki, Bartosz Frej |
| 2020 | GECCO | Comparative mixing for DSMGA-II. | Marcin M. Komarnicki, Michal Witold Przewozniczek, Tomasz M. Durda |
| 2020 | GECCO | On measuring and improving the quality of linkage learning in modern evolutionary algorithms applied to solve partially additively separable problems. | Michal Witold Przewozniczek, Bartosz Frej, Marcin M. Komarnicki |
| 2020 | GECCO | Empirical linkage learning. | Michal Witold Przewozniczek, Marcin M. Komarnicki |
| 2019 | GECCO | Parameter-less, population-sizing DSMGA-II. | Marcin M. Komarnicki, Michal Witold Przewozniczek |
| 2019 | GECCO | Parameter-less population pyramid with automatic feedback. | Adam M. Zielinski, Marcin M. Komarnicki, Michal Witold Przewozniczek |
| 2018 | GECCO | The influence of fitness caching on modern evolutionary methods and fair computation load measurement. | Michal Witold Przewozniczek, Marcin M. Komarnicki |
| 2017 | ACIIDS | The Effectiveness of the Simplicity in Evolutionary Computation. | Michal Witold Przewozniczek, Krzysztof Walkowiak, Michal Aibin |
| 2017 | CEC | Problem Encoding Allowing Cheap Fitness Computation of Mutated Individuals. | Michal Witold Przewozniczek |
| 2017 | GECCO | Parameter-less population pyramid with feedback. | Marcin M. Komarnicki, Michal Witold Przewozniczek |