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Conference
publications
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 M. W. Przewozniczek, F. Chicano, R. Tinós, J. Nalepa, B. Ruszczak, and
A. M. Wijata, On Revealing the
Hidden Problem Structure in Real-World and Theoretical Problems Using Walsh
Coefficient Influence, In Proceedings
of the Genetic and Evolutionary Computation Conference (GECCO '25), 2025 (in press).
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S. L. Thomson, M. W. Przewozniczek, Subfunction Structure Matters: A New
Perspective on Local Optima Networks, In Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO '25), 2025 (in
press).
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 J. Piątek, M. W. Przewozniczek,
F. Chicano, and R. Tinós, Moving
between high-quality optima using multi-satisfiability characteristics in
hard-to-solve Max3Sat instances, In Proceedings
of the Genetic and Evolutionary Computation Conference (GECCO '25), 2025 (in press).
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 J. Maciążek, M. W.
Przewozniczek, and J. Schwaab, Seeking
and leveraging alternative variable dependency concepts in gray-box-elusive
bimodal land-use allocation problems, In Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO '25), 2025 (in
press).
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A. M. Wijata, M. Bieńkowska, M. W. Przewozniczek, J. Nalepa,
Genetic Feature Selection for Multimodal Wound Detection, In Proceedings
of the Genetic and Evolutionary Computation Conference Companion (GECCO '25),
ACM, 2025 (in press).
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A. M. Wijata, N. Longépé, M. W. Przewozniczek, J. Nalepa, Machine Learning
and Genetic Algorithms: An Intricate Relationship for Locating Methane in
Satellite Images, In Proceedings of the Genetic and
Evolutionary Computation Conference Companion (GECCO '25), ACM, 2025 (in press).
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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.
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 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 (GECCO '24), pp. 412–421, 2024.
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 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.
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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 .
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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.
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M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka, K.
Walkowiak, Incremental
Recursive Ranking Grouping - A Decomposition Strategy for Additively and Nonadditively Separable Problems, In Proceedings of the Genetic and
Evolutionary Computation Conference Companion (GECCO '23), pp. 27-28,
ACM, 2023.
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 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.
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M. W. Przewozniczek, R. Tinós, B. Frej,M. M. Komarnicki, On turning Black- into
Dark Gray-optimization with the Direct Empirical
Linkage Discovery and Partition Crossover, In Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO '22), pp. 269–277, ACM, 2022.
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M. W. Przewozniczek,  M. M. Komarnicki, "Empirical linkage learning for
non-binary discrete search spaces in the optimization of a large-scale
real-world problem," in Proceedings of the 2022 Genetic and Evolutionary Computation Conference
Companion (GECCO '22), pp. 34-35, ACM, 2022.
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M. W. Przewozniczek,M. M. Komarnicki,
P. A. N. Bosman, D. Thierens, B. Frej, N. H. Luong, Hybrid Linkage Learning
for Permutation Optimization with Gene-pool Optimal Mixing Evolutionary
Algorithms, in Proceedings of the
2021 Genetic and Evolutionary Computation Conference Companion (GECCO ’21),
ACM, pp. 1442–1450, 2021.
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M.W. Przewozniczek,M. M. Komarnicki,
B. Frej, Direct linkage
discovery with empirical linkage learning, in Proceedings of the 2021 Genetic and Evolutionary Computation
Conference (GECCO ’21), ACM, pp. 609–617, 2021.
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M. W. Przewozniczek, P. Dziurzanski,
S. Zhao, L. S. Indrusiak, Multi-Objective
Parameter-less Population Pyramid in Solving the Real-World and Theoretical
Problems, in Proceedings of the 2021
Genetic and Evolutionary Computation Conference Companion (GECCO ’21). ACM, pp. 41-42,
2021.
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M. W. Przewozniczek,M. M. Komarnicki, Fitness caching - from
a minor mechanism to major consequences in modern evolutionary computation,
in Proceedings of the IEEE Congress on
Evolutionary Computation (CEC), pp. 1785-1791,
2021.
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M. W. Przewozniczek, B. Frej,M. M.
Komarnicki, On measuring and
improving the quality of linkage learning in modern evolutionary algorithms
applied to solve partially additively separable problems, in Proceedings of the 2020 Genetic and
Evolutionary Computation Conference (GECCO ’20). ACM, pp. 742–750, 2020.
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M. M.
Komarnicki, M. W. Przewozniczek,T. Durda, Comparative Mixing for
DSMGA-II, in Proceedings of the
2020 Genetic and Evolutionary Computation Conference (GECCO ’20), ACM,
pp. 708–716, 2020.
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S. Wozniak, M.
W. Przewozniczek,M. M. Komarnicki, Parameter-less
population pyramid for permutation-based problems, in Proceedings of the Parallel Problem
Solving from Nature (PPSN XVI), pp. 418-430, 2020.
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S. Zhao P. Dziurzanski, M. W. Przewozniczek,M. Komarnicki, L.S. Indrusiak, Cloud-based Dynamic
Distributed Optimisation of Integrated Process Planning and Scheduling in
Smart Factories, Proceedings of the
Genetic and Evolutionary Computation Conference, (GECCO 19), pp.
1381-1389, 2019.
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A. M.
Zieliński,M. M.
Komarnicki and M. W. Przewozniczek,
Parameter-less
population pyramid with automatic feedback, Proceedings of the Genetic and Evolutionary Computation Conference
Companion, (GECCO 19), pp. 312-313, 2019.
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S. Zhao, H. Mei,
P. Dziurzanski, M. W. Przewozniczek,
L.S. Indrusiak, Cloud-Based
Integrated Process Planning and Scheduling Optimisation via Asynchronous
Islands, in: Djemame K., Altmann J.,
Bañares J., Agmon Ben-Yehuda
O., Naldi M. (eds)
Economics of Grids, Clouds, Systems, and Services. GECON 2019. Lecture Notes
in Computer Science, Vol. 11819. Springer, Cham, pp. 247-259, 2019.
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M. W. Przewozniczek,M. M.
Komarnicki, The practical
use of problem encoding allowing cheap fitness computation of mutated
individuals, Proceedings of the
2018 Federated Conference on Computer Science and Information Systems, (FedCSIS 2019), pp. 57-65, 2018.
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M. W. Przewozniczek,M. M. Komarnicki, The influence of
fitness caching on modern evolutionary methods and fair computation load
measurement, Proceedings of the
Genetic and Evolutionary Computation Conference Companion, (GECCO 18),
pp. 241-242, 2018.
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M. Przewozniczek, Problem encoding allowing
cheap fitness computation of mutated individuals, Proceedings of the IEEE Congress on Evolutionary Computation (CEC),
pp.308-316, 2017.
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M. M. Komarnicki M. W. Przewozniczek,
Parameter-less
population pyramid with feedback, Proceedings
of the Genetic and Evolutionary Computation Conference Companion, (GECCO 17),
pp. 109–110, 2017.
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M. W. Przewozniczek,
K. Walkowiak,M. Aibin, The
Effectiveness of the Simplicity in Evolutionary Computation, Intelligent Information and Database
Systems: 9th Asian Conference, ACIIDS 2017, pp. 392–402, 2017.
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M. M.
Komarnicki, M. W. Przewozniczek,
Linked Genes
Migration in Island Models, Proceedings
of the 8th International Joint Conference on Computational Intelligence,
IJCCI 2016, vol. 3, pp. 30-40, 2016.
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M. Przewozniczek, Dynamic Subpopulation
Number Control for Solving Routing and Spectrum Allocation Problems in
Elastic Optical Networks, Proceedings
of the Third European Network Intelligence Conference, ENIC, pp.257-264,
2016.
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M. Przewozniczek, Multi
population pattern searching algorithm for solving routing spectrum
allocation with joint unicast and anycast problem
in elastic optical networks, Proceedings
of the 16th International Conference on Intelligent data engineering and
automated learning - IDEAL 2015, Vol. 42, No. 21, pp.328-339, 2015.
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B. Fidrysiak, M. W. Przewozniczek,
Towards finding an
effective way of discrete problems solving: the particle swarm optimization,
genetic algorithm and linkage learning techniques hybrydization,
Proceedings of the 7th International
Joint Conference on Computational Intelligence, IJCCI 2015, vol. 1, pp.
228-236, 2015.
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M. Przewozniczek, Towards finding an
effective uniform and single point crossover balance for optimization of
Elastic Optical Networks, Proceedings
of The Second European Network Intelligence Conference, ENIC 2015,
pp.40-46, 2015.
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M. Przewoźniczek, K. Walkowiak,
Quasi-hierarchical
Evolutionary Algorithm for Flow Optimization Survivable MPLS Networks, Proceedings of the 7th International
Conference on Computational Science and Its Applications, ICCSA 2007, Lecture
Notes in Computer Science, Vol. 4707, Springer Verlag,
2007, s. 330-342, 2007.
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