











Conference
publications 






M. W. Przewozniczek,
R. Tinós, M. M. Komarnicki,
First
Improvement Hill Climber with Linkage Learning  on Introducing Dark GrayBox Optimization into Statistical Linkage Learning
Genetic Algorithms, In Proceedings
of the Genetic and Evolutionary Computation Conference (GECCO '23), pp. 946954,
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. 981989,
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.
955962, ACM, 2023. 



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. 2728, ACM,
2023. 




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



M. W. Przewozniczek, R. Tinós, B. Frej, M. M. Komarnicki, On turning Black
into Dark Grayoptimization 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. 



M. W. Przewozniczek, M. M.
Komarnicki, "Empirical linkage learning for nonbinary
discrete search spaces in the optimization of a largescale realworld
problem," in Proceedings of the 2022 Genetic and Evolutionary Computation
Conference Companion (GECCO '22), ACM, 2022. (in press) 



M. W. Przewozniczek,
M. M. Komarnicki, P. A. N. Bosman, D. Thierens, B. Frej, N. H. Luong,
Hybrid Linkage
Learning for Permutation Optimization with Genepool Optimal Mixing
Evolutionary Algorithms, in Proceedings
of the 2021 Genetic and Evolutionary Computation Conference Companion (GECCO
’21), ACM, pp. 1442–1450, 2021. 



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. 



M. W. Przewozniczek, P. Dziurzanski,
S. Zhao, L. S. Indrusiak, MultiObjective
Parameterless Population Pyramid in Solving the RealWorld and Theoretical
Problems, in Proceedings of the
2021 Genetic and Evolutionary Computation Conference Companion (GECCO ’21).
ACM,
pp. 4142, 2021. 




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. 17851791, 2021. 




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. 




M. M. Komarnicki, M. W. Przewozniczek,
T. Durda, Comparative Mixing for
DSMGAII, in Proceedings of the
2020 Genetic and Evolutionary Computation Conference (GECCO ’20), ACM,
pp. 708–716, 2020. 




S. Wozniak, M. W. Przewozniczek,
and M. M. Komarnicki, Parameterless
population pyramid for permutationbased problems, in Proceedings of the Parallel Problem
Solving from Nature (PPSN XVI), pp. 418430, 2020. 




S. Zhao P. Dziurzanski, M. W. Przewozniczek,
M. Komarnicki, L.S. Indrusiak,
Cloudbased Dynamic
Distributed Optimisation of Integrated Process Planning and Scheduling in
Smart Factories, Proceedings of the
Genetic and Evolutionary Computation Conference, (GECCO 19), pp.
13811389, 2019. 




A.M. Zieliński, M. M. Komarnicki
and M. W. Przewozniczek, Parameterless
population pyramid with automatic feedback, Proceedings of the Genetic and Evolutionary Computation Conference
Companion, (GECCO 19), pp. 312313, 2019. 




S. Zhao, H. Mei,
P. Dziurzanski, M. W. Przewozniczek,
L.S. Indrusiak, CloudBased
Integrated Process Planning and Scheduling Optimisation via Asynchronous
Islands, in: Djemame K., Altmann J.,
Bañares J., Agmon
BenYehuda O., Naldi M. (eds)
Economics of Grids, Clouds, Systems, and Services. GECON 2019. Lecture Notes
in Computer Science, Vol. 11819. Springer, Cham, pp. 247259, 2019. 




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. 5765, 2018. 




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. 241242, 2018. 




M. Przewozniczek, Problem encoding allowing
cheap fitness computation of mutated individuals, Proceedings of the IEEE Congress on Evolutionary Computation (CEC),
pp.308316, 2017. 




M. M. Komarnicki
M. W. Przewozniczek, Parameterless
population pyramid with feedback, Proceedings
of the Genetic and Evolutionary Computation Conference Companion, (GECCO 17),
pp. 109–110, 2017. 




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. 




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. 3040, 2016. 




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.257264,
2016. 




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.328339, 2015. 




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.
228236, 2015. 




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.4046, 2015. 




M. Przewoźniczek,
K. Walkowiak, Quasihierarchical
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. 330342, 2007. 

