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Conference
publications |
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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. 14421450, 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. 609617, 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, 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. 742750, 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. 708716, 2020. |
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S. Wozniak, M. W. Przewozniczek,
and 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.,
Baρares 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. 109110, 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. 392402, 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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