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Marcin Komarnicki
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2020 – today
- 2024
- [c20]Marcin Michal Komarnicki
, Michal Witold Przewozniczek
Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems. GECCO 2024 - [i2]Michal Witold Przewozniczek, Bartosz Frej, Marcin M. Komarnicki:
The hop-like problem nature - unveiling and modelling new features of real-world problems. CoRR abs/2406.01215 (2024) - 2023
- [j6]Marcin Michal Komarnicki
Incremental Recursive Ranking Grouping for Large-Scale Global Optimization. IEEE Trans. Evol. Comput. 27(5): 1498-1513 (2023) - [c19]Marcin Michal Komarnicki
Incremental Recursive Ranking Grouping - A Decomposition Strategy for Additively and Nonadditively Separable Problems. GECCO Companion 2023: 27-28 - [c18]Michal Witold Przewozniczek
First Improvement Hill Climber with Linkage Learning - on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms. GECCO 2023: 946-954 - [c17]Michal Witold Przewozniczek
To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary computation. GECCO 2023: 955-962 - 2022
- [c16]Michal Witold Przewozniczek, Marcin M. Komarnicki:
Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem. GECCO Companion 2022: 35-36 - [c15]Michal Witold Przewozniczek, Renato Tinós, Bartosz Frej, Marcin M. Komarnicki:
On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. GECCO 2022: 269-277 - [i1]Marcin Michal Komarnicki, Michal Witold Przewozniczek, Halina Kwasnicka
Incremental Recursive Ranking Grouping for Large Scale Global Optimization. CoRR abs/2206.04168 (2022) - 2021
- [j5]Michal Witold Przewozniczek
Empirical problem decomposition - the key to the evolutionary effectiveness in solving a large-scale non-binary discrete real-world problem. Appl. Soft Comput. 113(Part): 107864 (2021) - [c14]Michal Witold Przewozniczek
Fitness Caching - From a Minor Mechanism to Major Consequences in Modern Evolutionary Computation. CEC 2021: 1785-1791 - [c13]Michal Witold Przewozniczek
Direct linkage discovery with empirical linkage learning. GECCO 2021: 609-617 - [c12]Michal Witold Przewozniczek
Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. GECCO Companion 2021: 1442-1450 - 2020
- [j4]Michal Witold Przewozniczek
Splitting the fitness and penalty factor for temporal diversity increase in practical problem solving. Expert Syst. Appl. 145: 113126 (2020) - [j3]Piotr Dziurzanski
Scalable distributed evolutionary algorithm orchestration using Docker containers. J. Comput. Sci. 40: 101069 (2020) - [j2]Michal Witold Przewozniczek
Empirical Linkage Learning. IEEE Trans. Evol. Comput. 24(6): 1097-1111 (2020) - [c11]Michal Witold Przewozniczek
Empirical linkage learning. GECCO Companion 2020: 23-24 - [c10]Marcin M. Komarnicki
Comparative mixing for DSMGA-II. GECCO 2020: 708-716 - [c9]Michal Witold Przewozniczek
On measuring and improving the quality of linkage learning in modern evolutionary algorithms applied to solve partially additively separable problems. GECCO 2020: 742-750 - [c8]Szymon Wozniak
Parameter-Less Population Pyramid for Permutation-Based Problems. PPSN (1) 2020: 418-430
2010 – 2019
- 2019
- [j1]Michal Witold Przewozniczek
The transformation of the k-Shortest Steiner trees search problem into binary dynamic problem for effective evolutionary methods application. Inf. Sci. 479: 1-19 (2019) - [c7]Marcin M. Komarnicki
Parameter-less, population-sizing DSMGA-II. GECCO (Companion) 2019: 289-290 - [c6]Adam M. Zielinski, Marcin M. Komarnicki
Parameter-less population pyramid with automatic feedback. GECCO (Companion) 2019: 312-313 - [c5]Shuai Zhao, Piotr Dziurzanski
Cloud-based dynamic distributed optimisation of integrated process planning and scheduling in smart factories. GECCO 2019: 1381-1389 - 2018
- [c4]Michal Przewozniczek
The Practical Use of Problem Encoding Allowing Cheap Fitness Computation of Mutated Individuals. FedCSIS 2018: 57-65 - [c3]Michal Witold Przewozniczek
The influence of fitness caching on modern evolutionary methods and fair computation load measurement. GECCO (Companion) 2018: 241-242 - 2017
- [c2]Marcin M. Komarnicki, Michal Witold Przewozniczek:
Parameter-less population pyramid with feedback. GECCO (Companion) 2017: 109-110 - 2016
- [c1]Marcin Komarnicki
Linked Genes Migration in Island Models. IJCCI (ECTA) 2016: 30-40
Coauthor Index
aka: Michal Witold Przewozniczek
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