Evolutionary Algorithm for Congestion Problem in Connection-Oriented Networks. - Michal Przewozniczek; Krzysztof Walkowiak (ICCSA (4), 2005)

Quasi-hierarchical Evolutionary Algorithm for Flow Optimization in Survivable MPLS Networks. - Michal Przewozniczek; Krzysztof Walkowiak (ICCSA (3), 2007)

Modeling and optimization of survivable P2P multicasting. - Krzysztof Walkowiak; Michal Przewozniczek (Comput. Commun., 2011)

Optimizing distributed computing systems for k-nearest neighbours classifiers - evolutionary approach. - Michal Przewozniczek; Krzysztof Walkowiak; Michal Wozniak 001 (Log. J. IGPL, 2011)

Multi Population Pattern Searching Algorithm: A New Evolutionary Method Based on the Idea of Messy Genetic Algorithm. - Halina Kwasnicka; Michal Przewozniczek (IEEE Trans. Evol. Comput., 2011)

Heuristic Algorithms for Survivable P2P Multicasting. - Krzysztof Walkowiak; Michal Przewozniczek; Krzysztof Pajak (Appl. Artif. Intell., 2013)

Towards Finding an Effective Uniform and Single Point Crossover Balance for Optimization of Elastic Optical Networks. - Michal Przewozniczek (ENIC, 2015)

Constructive heuristics for technology-driven Resource Constrained Scheduling Problem. - Pawel B. Myszkowski; Michal Przewozniczek; Marek Skowronski (FedCSIS, 2015)

Multi Population Pattern Searching Algorithm for Solving Routing Spectrum Allocation with Joint Unicast and Anycast Problem in Elastic Optical Networks. - Michal Przewozniczek (IDEAL, 2015)

Towards Finding an Effective Way of Discrete Problems Solving: The Particle Swarm Optimization, Genetic Algorithm and Linkage Learning Techniques Hybrydization. - Bartosz Andrzej Fidrysiak; Michal Przewozniczek (IJCCI (ECTA), 2015)

Towards solving practical problems of large solution space using a novel pattern searching hybrid evolutionary algorithm - An elastic optical network optimization case study. - Michal Przewozniczek; Róza Goscien; Krzysztof Walkowiak; Miroslaw Klinkowski (Expert Syst. Appl., 2015)

Dynamic Subpopulation Number Control for Solving Routing and Spectrum Allocation Problems in Elastic Optical Networks. - Michal Przewozniczek (ENIC, 2016)

Linked Genes Migration in Island Models. - Marcin Komarnicki; Michal Przewozniczek (IJCCI (ECTA), 2016)

Active Multi-Population Pattern Searching Algorithm for flow optimization in computer networks - The novel coevolution schema combined with linkage learning. - Michal Przewozniczek (Inf. Sci., 2016)

The Effectiveness of the Simplicity in Evolutionary Computation. - Michal Witold Przewozniczek; Krzysztof Walkowiak; Michal Aibin (ACIIDS (2), 2017)

Problem Encoding Allowing Cheap Fitness Computation of Mutated Individuals. - Michal Witold Przewozniczek (CEC, 2017)

Parameter-less population pyramid with feedback. - Marcin M. Komarnicki; Michal Witold Przewozniczek (GECCO (Companion), 2017)

The evolutionary cost of Baldwin effect in the routing and spectrum allocation problem in elastic optical networks. - Michal Witold Przewozniczek; Krzysztof Walkowiak; Michal Aibin (Appl. Soft Comput., 2017)

The Practical Use of Problem Encoding Allowing Cheap Fitness Computation of Mutated Individuals. - Michal Przewozniczek; Marcin Komarnicki (FedCSIS, 2018)

The influence of fitness caching on modern evolutionary methods and fair computation load measurement. - Michal Witold Przewozniczek; Marcin M. Komarnicki (GECCO (Companion), 2018)

Cloud-based dynamic distributed optimisation of integrated process planning and scheduling in smart factories. - Shuai Zhao 004; Piotr Dziurzanski; Michal Przewozniczek; Marcin Komarnicki; Leandro Soares Indrusiak (GECCO, 2019)

Parameter-less, population-sizing DSMGA-II. - Marcin M. Komarnicki; Michal Witold Przewozniczek (GECCO (Companion), 2019)

Parameter-less population pyramid with automatic feedback. - Adam M. Zielinski; Marcin M. Komarnicki; Michal Witold Przewozniczek (GECCO (Companion), 2019)

Cloud-Based Integrated Process Planning and Scheduling Optimisation via Asynchronous Islands. - Shuai Zhao 004; Haitao Mei 001; Piotr Dziurzanski; Michal Przewozniczek; Leandro Soares Indrusiak (GECON, 2019)

Universal strategy of dynamic subpopulation number management in practical network optimization problems. - Michal Witold Przewozniczek; Róza Goscien (Appl. Soft Comput., 2019)

The transformation of the k-Shortest Steiner trees search problem into binary dynamic problem for effective evolutionary methods application. - Michal Witold Przewozniczek; Krzysztof Walkowiak; Arunabha Sen; Marcin Komarnicki; Piotr Lechowicz (Inf. Sci., 2019)

Comparative mixing for DSMGA-II. - Marcin M. Komarnicki; Michal Witold Przewozniczek; Tomasz M. Durda (GECCO, 2020)

On measuring and improving the quality of linkage learning in modern evolutionary algorithms applied to solve partially additively separable problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin M. Komarnicki (GECCO, 2020)

Parameter-Less Population Pyramid for Permutation-Based Problems. - Szymon Wozniak; Michal Przewozniczek; Marcin M. Komarnicki (PPSN (1), 2020)

Metaheuristic algorithms with solution encoding mixing for effective optimization of SDM optical networks. - Michal Witold Przewozniczek; Róza Goscien; Piotr Lechowicz; Krzysztof Walkowiak (Eng. Appl. Artif. Intell., 2020)

Splitting the fitness and penalty factor for temporal diversity increase in practical problem solving. - Michal Witold Przewozniczek; Rituparna Datta; Krzysztof Walkowiak; Marcin Michal Komarnicki (Expert Syst. Appl., 2020)

Subpopulation initialization driven by linkage learning for dealing with the Long-Way-To-Stuck effect. - Michal Witold Przewozniczek (Inf. Sci., 2020)

Scalable distributed evolutionary algorithm orchestration using Docker containers. - Piotr Dziurzanski; Shuai Zhao 004; Michal Przewozniczek; Marcin Komarnicki; Leandro Soares Indrusiak (J. Comput. Sci., 2020)

Empirical Linkage Learning. - Michal Witold Przewozniczek; Marcin Michal Komarnicki (IEEE Trans. Evol. Comput., 2020)

Fitness Caching - From a Minor Mechanism to Major Consequences in Modern Evolutionary Computation. - Michal Witold Przewozniczek; Marcin M. Komarnicki (CEC, 2021)

Multi-objective parameter-less population pyramid in solving the real-world and theoretical problems. - Michal Witold Przewozniczek; Piotr Dziurzanski; Shuai Zhao 004; Leandro Soares Indrusiak (GECCO Companion, 2021)

Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. - Michal Witold Przewozniczek; Marcin M. Komarnicki; Peter A. N. Bosman; Dirk Thierens; Bartosz Frej; Ngoc Hoang Luong (GECCO Companion, 2021)

Direct linkage discovery with empirical linkage learning. - Michal Witold Przewozniczek; Marcin Michal Komarnicki; Bartosz Frej (GECCO, 2021)

Empirical problem decomposition - the key to the evolutionary effectiveness in solving a large-scale non-binary discrete real-world problem. - Michal Witold Przewozniczek; Marcin Michal Komarnicki (Appl. Soft Comput., 2021)

Multi-Objective parameter-less population pyramid for solving industrial process planning problems. - Michal Witold Przewozniczek; Piotr Dziurzanski; Shuai Zhao 004; Leandro Soares Indrusiak (Swarm Evol. Comput., 2021)

Empirical linkage learning for non-binary discrete search spaces in the optimization of a large-scale real-world problem. - Michal Witold Przewozniczek; Marcin M. Komarnicki (GECCO Companion, 2022)

On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. - Michal Witold Przewozniczek; Renato Tinós; Bartosz Frej; Marcin M. Komarnicki (GECCO, 2022)

Iterated local search with perturbation based on variables interaction for pseudo-boolean optimization. - Renato Tinós; Michal Witold Przewozniczek; Darrell Whitley (GECCO, 2022)

Incremental Recursive Ranking Grouping for Large Scale Global Optimization. - Marcin Michal Komarnicki; Michal Witold Przewozniczek; Halina Kwasnicka (CoRR, 2022)

Incremental Recursive Ranking Grouping - A Decomposition Strategy for Additively and Nonadditively Separable Problems. - Marcin Michal Komarnicki; Michal Witold Przewozniczek; Halina Kwasnicka; Krzysztof Walkowiak (GECCO Companion, 2023)

To slide or not to slide? Moving along fitness levels and preserving the gene subsets diversity in modern evolutionary computation. - Michal Witold Przewozniczek; Marcin Michal Komarnicki (GECCO, 2023)

First Improvement Hill Climber with Linkage Learning - on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms. - Michal Witold Przewozniczek; Renato Tinós; Marcin Michal Komarnicki (GECCO, 2023)

Genetic Algorithm with Linkage Learning. - Renato Tinós; Michal Przewozniczek; Darrell Whitley; Francisco Chicano (GECCO, 2023)

Incremental Recursive Ranking Grouping for Large-Scale Global Optimization. - Marcin Michal Komarnicki; Michal Witold Przewozniczek; Halina Kwasnicka; Krzysztof Walkowiak (IEEE Trans. Evol. Comput., 2023)

Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems. - Marcin Michal Komarnicki; Michal Witold Przewozniczek; Renato Tinós; Xiaodong Li 001 (GECCO, 2024)

CANNIBAL Unveils the Hidden Gems: Hyperspectral Band Selection via Clustering of Weighted Variable Interaction Graphs. - Lukasz Tulczyjew; Michal Przewozniczek; Renato Tinós; Agata M. Wijata; Jakub Nalepa (GECCO, 2024)

The hop-like problem nature - unveiling and modelling new features of real-world problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin M. Komarnicki (CoRR, 2024)

Replication package of the paper "Iterated Local Search with Linkage Learning" published in ACM Transactions on Evolutionary Learning and Optimization 4(2): 1-29. - Renato Tinós; Michal Witold Przewozniczek; Darrell Whitley; Francisco Chicano (Zenodo, 2024)

Replication package of the paper "Iterated Local Search with Linkage Learning" published in ACM Transactions on Evolutionary Learning and Optimization 4(2): 1-29. - Renato Tinós; Michal Witold Przewozniczek; Darrell Whitley; Francisco Chicano (Zenodo, 2024)

Iterated Local Search with Linkage Learning. - Renato Tinós; Michal Witold Przewozniczek; Darrell Whitley; Francisco Chicano (ACM Trans. Evol. Learn. Optim., 2024)

Seeking and leveraging alternative variable dependency concepts in gray-box-elusive bimodal land-use allocation problems. - Jakub Maciazek; Michal Przewozniczek; Jonas Schwaab (GECCO, 2025)

Moving between high-quality optima using multi-satisfiability characteristics in hard-to-solve Max3Sat instances. - Jedrzej Piatek; Michal Witold Przewozniczek; Francisco Chicano; Renato Tinós (GECCO, 2025)

On Revealing the Hidden Problem Structure in Real-World and Theoretical Problems Using Walsh Coefficient Influence. - Michal Witold Przewozniczek; Francisco Chicano; Renato Tinós; Jakub Nalepa; Bogdan Ruszczak; Agata Wijata (GECCO, 2025)

Subfunction Structure Matters: A New Perspective on Local Optima Networks. - Sarah L. Thomson; Michal Witold Przewozniczek (GECCO, 2025)

Pareto Front Improvements Phase using linkage learning and mating restrictions for solving multi-objective industrial process planning problems with low-sized pareto fronts. - Szymon Niemczyk; Michal Witold Przewozniczek; Piotr Dziurzanski (Expert Syst. Appl., 2025)

Availability of Perfect Decomposition in Statistical Linkage Learning for Unitation-based Function Concatenations. - Michal Prusik; Bartosz Frej; Michal Witold Przewozniczek (CoRR, 2025)

Subfunction Structure Matters: A New Perspective on Local Optima Networks. - S. L. Thomson; Michal Witold Przewozniczek (CoRR, 2025)

From Direct to Directional Variable Dependencies - Nonsymmetrical Dependencies Discovery in Real-World and Theoretical Problems. - Michal Witold Przewozniczek; Bartosz Frej; Marcin Michal Komarnicki (IEEE Trans. Evol. Comput., 2025)