Tutorials

 

 

 

 

 

 

M.W. Przewozniczek, M. M. Komarnicki

From White to Black through Gray... and one step back to Dark Gray.

All colors of model-building optimization.

2023

 

 

M.W. Przewozniczek, M. M. Komarnicki

Modern Linkage Learning Techniques in Combinatorial Optimization’22

2022

 

 

M.W. Przewozniczek, M. M. Komarnicki

Modern Linkage Learning Techniques in Combinatorial Optimization’21

2021

 

 

 

 

 

 

 

 

 

 

Awards and nominations

 

 

 

 

 

 

M. W. Przewozniczek, R. Tinós, M. M. Komarnicki, First Improvement Hill Climber with Linkage Learning -- on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23), pp. 946-954, ACM, 2023.

 

 

R. Tinós, M. W. Przewozniczek, D. Whitley, Iterated Local Search with Perturbation based on Variables Interaction for Pseudo-Boolean Optimization, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '22), pp. 296–304, ACM, 2022.

 

 

 

 

 

 

 

 

 

 

IEEE Transactions on Evolutionary Computation

 

 

 

 

 

M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka and K. Walkowiak, Incremental Recursive Ranking Grouping for Large Scale Global Optimization, IEEE Transactions on Evolutionary Computation, vol. 27, pp. 1498–1513, 2023.

 

 

M.W. Przewozniczek, M. M. Komarnicki, Empirical linkage learning, IEEE Transactions on Evolutionary Computation,  vol. 24, no. 6, pp. 1097-1111, 2020.

 

 

 

*H. Kwasnicka, M. Przewozniczek, Multi Population Pattern Searching Algorithm: a new evolutionary method based on the idea of messy Genetic Algorithm, IEEE Transactions on Evolutionary Computation, Vol. 15, No.5, pp. 715-734, 2011.

*The order of the authors is alphabetical; The main author is Michal Przewozniczek, and the paper is the core of his PhD thesis.

 

 

 

 

 

 

 

 

 

 

 

Recent publications (since 2023)

 

 

 

 

 

Journals

 

 

 

 

 

 

 

R. Tinós, M. W. Przewozniczek, D. Whitley, and F. Chicano, Iterated Local Search with Linkage Learning, ACM Transactions on Evolutionary Learning and Optimization, Vol. 4, Issue 2, pp. 1-29, 2024.

 

 

 

M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka and K. Walkowiak, Incremental Recursive Ranking Grouping for Large Scale Global Optimization, IEEE Transactions on Evolutionary Computation, vol. 27, pp. 1498–1513, 2023.

 

 

MORE…

 

 

 

 

 

 

 

Conferences

 

 

 

 

 

 

 

M. M. Komarnicki, M. W. Przewozniczek, R. Tinós, and X. Li, Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '24), pp. 665–673, 2024.

 

 

L. Tulczyjew, M. W. Przewozniczek, R. Tinós, A. M. Wijata, and J. Nalepa, CANNIBAL Unveils the Hidden Gems: Hyperspectral Band Selection via Clustering of Weighted Variable Interaction Graphs, In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '23), pp. 412–421, 2024.

 

 

M. W. Przewozniczek, R. Tinós, M. M. Komarnicki, First Improvement Hill Climber with Linkage Learning -- on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23), pp. 946-954, ACM, 2023.

 

 

R. Tinós, M. W. Przewozniczek, D. Whitley, F. Chicano, Genetic Algorithm with Linkage Learning, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23), pp. 981-989, ACM, 2023 .

 

 

M. W. Przewozniczek, M. M. Komarnicki, To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary algorithms, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23), pp. 955-962, ACM, 2023.

 

 

MORE…

 

 

 

 

 

 

 

 

 

 

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