Byrski, Aleksander
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Item type:Article, Access status: Open Access , Population diversity in ant-inspired optimization algorithms(Wydawnictwa AGH, 2021) Byrski, Aleksander; Węgrzyński, Krzysztof; Radwański, Wojciech; Starzec, Grażyna; Starzec, Mateusz; Bargiel, Monika; Urbańczyk, Aleksandra; Kisiel-Dorohinicki, MarekMeasuring the diversity in evolutionary algorithms that work in real-value search spaces is often computationally complex, but it is feasible, however, measuring the diversity in combinatorial domains is practically impossible. Nevertheless, in this paper we propose several practical and feasible diversitymeasurement techniques that are dedicated to ant colony optimization algorithms, leveraging the fact that we can focus on a pheromone table even though an analysis of the search space is at least an NP problem where the direct outcomes of the search are expressed and can be analyzed. Besides sketching out the algorithms, we apply them to several benchmark problems and discuss their efficacy.Item type:Article, Access status: Open Access , Emergence of population structure in socio-cognitively inspired ant colony optimization(Wydawnictwa AGH, 2018) Byrski, Aleksander; Świderska, Ewelina; Łasisz, Jakub; Kisiel-Dorohinicki, Marek; Lenaerts, Tom; Samson, Dana; Indurkhya, BipinA metaheuristic proposed by us recently, Ant Colony Optimization (ACO) hybridized with socio-cognitive inspirations, turned out to generate interesting results compared to classic ACO. Even though it does not always find better solutions to the considered problems, it usually finds sub-optimal solutions usually. Moreover, instead of a trial-and-error approach to configure the parameters of the ant species in the population, in our approach, the actual structure of the population emerges from predefined species-to-species ant migration strategies. Experimental results of our approach are compared against classic ACO and selected socio-cognitive versions of this algorithm.Item type:Article, Access status: Open Access , Maximizing efficiency: a comparative study of SOMA variants and constraint handling methods for time delay system optimization(2023) Senkerik, Roman; Kadavy, Tomas; Janku, Peter; Pluhacek, Michal; Guzowski, Hubert; Pekar, Libor; Matusu, Radek; Viktorin, Adam; Smołka, Maciej; Byrski, Aleksander; Komínková Oplatková, Zuzana
Wydział InformatykiThis paper presents an experimental study that compares four adaptive variants of the self-organizing migrating algorithm (SOMA). Each variant uses three different constraint handling methods for the optimization of a time delay system model. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delayed systems to develop more effective and efficient control strategies and precise model identifications. The study includes a detailed description of the selected variants of the SOMA and the adaptive mechanisms used. A complex workflow of experiments is described, and the results and discussion are presented. The experimental results highlight the effectiveness of the SOMA variants with specific constraint handling methods for time delay system optimization. Overall, this study contributes to the understanding of the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of the SOMA variants and can help guide the selection of appropriate constraint handling methods and the adaptive mechanisms of metaheuristics.Item type:Article, Access status: Open Access , Tuning of agent-based computing(Wydawnictwa AGH, 2013) Byrski, AleksanderIn this paper, an Evolutionary Multi-agent system-based computing process is subjected to a detailed analysis of its parameters in order to establish a base for a better understanding of the meta-heuristics from the practitioner’s point of view. After reviewing the concepts of EMAS and its immunological variant, a series of experiments is shown, and results of the influence of the search outcomes by certain parameters is discussed.Item type:Article, Access status: Open Access , Volunteer computing simulation using RePast and MASON(Wydawnictwa AGH, 2013) Byrski, Aleksander; Feluś, Michał; Gawlik, Jakub; Jasica, Rafał; Kobak, Paweł; Jankowski, Grzegorz; Nawarecki, Edward; Wroczyński, Michał; Majewski, Przemysław; Krupa, Tomasz; Strychalski, JacekVolunteer environments usually consist of a large number of computing nodes, with highly dynamic characteristics, therefore reliable models for a planning of the whole computing are highly desired. An easy to implement approach to modelling and simulation of such environments May employ agent-based universal simulation frameworks, such as RePast or MASON. In the course of the paper the above-mentioned simulation frame Works are adapter to suport simulation of volunteer computing. After giving implementation details, selected results concerning computing time and speedup are given and are compared with the ones obtained from an actual volunteer environment.Item type:Article, Access status: Open Access , Model for dynamic and hierarchical data repository in relational database(Wydawnictwa AGH, 2018) Piech, Mateusz; Frącz, Wojciech; Turek, Wojciech; Kisiel-Dorohinicki, Marek; Dajda, Jacek; Byrski, AleksanderThe aim of this research is to build an open schema model for a digital sources repository in a relational database. This required us to develop a few advanced techniques. One of them was to keep and maintain a hierarchical data structure pushed into the repository. A second was to create constraints on any hierarchical level that allows for the enforcement of data integrity and consistency. The created solution is mainly based on a JSON file as a native column type, which was designed for holding open schema documents. In this paper, we present a model for any repository that uses hierarchical dynamic data. Additionally, we include a structure for normalizing the input and description for the data in order to keep all of the model assumptions. We compared our solution with a well-known open schema model – Entity-Attribute-Value - in the scope of saving data and querying about relationships and contents from the structure. The results show that we achieved improvements in both the performance and disk space usage, as we extended our model with a few new features that the previous model does not include. The techniques developed in this research can be applied in every domain where hierarchical dynamic data is required, as demonstrated by the digital book repository that we have presented.Item type:Article, Access status: Open Access , Hybrid neuro-fuzzy classifier based on NEFCLASS model(Wydawnictwa AGH, 2011) Gliwa, Bogdan; Byrski, AleksanderThe paper presents hybrid neuro-fuzzy classifier, based on NEFCLASS model, which was modified. The presented classifier was compared to popular classifiers - neural networks and k-nearest neighbours. Efficiency of modifications in classifier was compared with methods used in original model NEFCLASS (learning methods). Accuracy of classifier was tested using 3 datasets from UCI Machine Learning Repository: iris, wine and breast cancer wis-consin. Moreover, influence of ensemble classification methods on classification accuracy was presented.Item type:Article, Access status: Open Access , Optimization of simulation model parameters for solidification of metals with use of agent-based evolutionary algorithm(Wydawnictwa AGH, 2008) Kluska-Nawarecka, Stanisława; Smolarek-Grzyb, Agnieszka; Byrski, Aleksander; Wilk-Kołodziejczyk, DorotaThe finite elements method (FEM) is currently widely used for simulation of thermal processes. However, one of still unresolved problems remains proper selection of mathematical model parameters for these processes. As far as modelling of cooling casts in forms is concerned, particular difficulties appear while estimating values of numerous coefficients such as: heat transport coefficient between metal and form, specific heat, metal and form heat conduction coefficient, metal and form density. Coefficients mentioned above depend not only on materials properties but also on temperature. In the paper the idea of optimalization of simulation method parameters based on adaptive adjustment of curve representing simulation result and result obtained in physical experiment is presented along with the idea of evolutionary and agent-based evolutionary optimization system designed to conduct such optimizations. Preliminary results obtained with use of ABAQUS system available in ACK CYFRONET and software developed at AGH-UST conclude the paper.Item type:Article, Access status: Open Access , A crisis management approach to mission survivability in computational multi-agent systems(Wydawnictwa AGH, 2010) Byrski, Aleksander; Kisiel-Dorohinicki, Marek; Carvalho, MarcoIn this paper we present a biologically-inspired approach for mission survivability (considered as the capability of fulfilling a task such as computation) that allows the system to be aware of the possible threats or crises that may arise. This approach uses the notion of resources used by living organisms to control their populations. We present the concept of energetic selection in agent-based evolutionary systems as well as the means to manipulate the configuration of the computation according to the crises or user's specific demands.Item type:Article, Access status: Open Access , Efficient time-delay system optimization with auto-configured metaheuristics(2024) Senkerik, Roman; Guzowski, Hubert; Janku, Peter; Kadavy, Tomas; Kominkova Oplatkova, Zuzana; Matusu, Radek; Pluhacek, Michal; Pekar, Libor; Viktorin, Adam; Byrski, Aleksander; Smołka, Maciej
Wydział InformatykiThis paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics.