Projects funded by the NCN


Information on the principal investigator and host institution

Information of the project and the call

Keywords

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Development of evolutionary methods dedicated to solving multi- and many-objective problems with the use of linkage learning techniques.

2020/38/E/ST6/00370

Keywords:

linkage learning multi-objective optimization many-objective optimization linkage diversity Pareto front clusterization

Descriptors:

  • ST6_7: Artificial intelligence, intelligent systems, multi-agent systems

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Politechnika Wrocławska

woj.

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr Michał Witold Przewoźniczek 

Number of co-investigators in the project: 4

Call: SONATA BIS 10 - announced on 2020-07-29

Amount awarded: 1 426 800 PLN

Project start date (Y-m-d): 2021-07-01

Project end date (Y-m-d): 2026-06-30

Project duration:: 60 months (the same as in the proposal)

Project status: Pending project

Project description

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Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Information in the final report

  • Publication in academic press/journals (3)
  • Articles in post-conference publications (6)
  1. Incremental Recursive Ranking Grouping for Large Scale Global Optimization
    Authors:
    M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka and K. Walkowiak
    Academic press:
    IEEE Transactions on Evolutionary Computation (rok: 2022, tom: bd, strony: bd), Wydawca: IEEE
    Status:
    Published
    DOI:
    10.1109/TEVC.2022.3216968 - link to the publication
  2. Incremental Recursive Ranking Grouping for Large Scale Global Optimization
    Authors:
    M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka and K. Walkowiak
    Academic press:
    IEEE Transactions on Evolutionary Computation (rok: 2022, tom: bd, strony: bd), Wydawca: IEEE
    Status:
    Published
    DOI:
    10.1109/TEVC.2022.3216968 - link to the publication
  3. Balancing Pareto Front exploration of Non-dominated Tournament Genetic Algorithm (B-NTGA) in solving multi-objective NP-hard problems with constraints
    Authors:
    Michał Antkiewicz, Paweł B. Myszkowski
    Academic press:
    Information Sciences (rok: 2024, tom: 667, strony: b.d.), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.ins.2024.120400 - link to the publication
  1. Incremental Recursive Ranking Grouping - A Decomposition Strategy for Additively and Nonadditively Separable Problems
    Authors:
    M. M. Komarnicki, M. W. Przewozniczek, H. Kwasnicka, K. Walkowiak
    Conference:
    Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '23) (rok: 2023, tom: GECCO, strony: 27-28), Wydawca: ACM
    Data:
    konferencja July 15-19, 2023
    Status:
    Published
    DOI:
    10.1145/3583133.3595846 - link to the publication
  2. On turning Black- into Dark Gray-optimization with the Direct Empirical Linkage Discovery and Partition Crossover
    Authors:
    M. W. Przewozniczek, R. Tinos, B. Frej, M. M. Komarnicki
    Conference:
    Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '22) (rok: 2022, tom: Genetic and Evolutionary Computation Conference (GECCO '22), strony: 269–277), Wydawca: ACM
    Data:
    konferencja 2022.07.09-13
    Status:
    Published
    DOI:
    10.1145/3512290.3528734 - link to the publication
  3. To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary algorithms
    Authors:
    M. W. Przewozniczek, M. M. Komarnicki
    Conference:
    Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '23) (rok: 2023, tom: GECCO, strony: 955-962), Wydawca: ACM
    Data:
    konferencja July 15-19, 2023
    Status:
    Published
    DOI:
    10.1145/3583131.3590491 - link to the publication
  4. Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem
    Authors:
    M. W. Przewozniczek, M. M. Komarnicki
    Conference:
    Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion (GECCO '22) (rok: 2022, tom: Genetic and Evolutionary Computation Conference (GECCO '22), strony: 35–36), Wydawca: ACM
    Data:
    konferencja 2022.07.09-13
    Status:
    Published
    DOI:
    10.1145/3520304.3534059 - link to the publication
  5. On turning Black- into Dark Gray-optimization with the Direct Empirical Linkage Discovery and Partition Crossover
    Authors:
    M. W. Przewozniczek, R. Tinos, B. Frej, M. M. Komarnicki
    Conference:
    Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '22) (rok: 2022, tom: Genetic and Evolutionary Computation Conference (GECCO '22), strony: 269–277), Wydawca: ACM
    Data:
    konferencja 2022.07.09-13
    Status:
    Published
    DOI:
    10.1145/3512290.3528734 - link to the publication
  6. Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem
    Authors:
    M. W. Przewozniczek, M. M. Komarnicki
    Conference:
    Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion (GECCO '22) (rok: 2022, tom: Genetic and Evolutionary Computation Conference (GECCO '22), strony: 35–36), Wydawca: ACM
    Data:
    konferencja 2022.07.09-13
    Status:
    Published
    DOI:
    10.1145/3520304.3534059 - link to the publication