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    Wyświetlanie 1-9 z 9
    Tytuł:
    Interactive evolutionary multiobjective optimization driven by robust ordinal regression
    Autorzy:
    Branke, J.
    Greco, S.
    Słowiński, R.
    Zielniewicz, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/200702.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    evolutionary multiobjective optimization
    interactive procedure
    robust ordinal regression
    Opis:
    This paper presents the Necessary-preference-enhanced Evolutionary Multiobjective Optimizer (NEMO), which combines an evolutionary multiobjective optimization with robust ordinal regression within an interactive procedure. In the course of NEMO, the decision maker is asked to express preferences by simply comparing some pairs of solutions in the current population. The whole set of additive value functions compatible with this preference information is used within a properly modified version of the evolutionary multiobjective optimization technique NSGA-II in order to focus the search towards solutions satisfying the preferences of the decision maker. This allows to speed up convergence to the most preferred region of the Pareto-front.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2010, 58, 3; 347-358
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evolutionary algorithms for global parametric fault diagnosis in analogue integrated circuits
    Autorzy:
    Jantos, P.
    Grzechca, D.
    Rutkowski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/201078.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    analogue integrated circuits
    fault diagnosis
    localization
    identification
    evolutionary algorithms
    Opis:
    An evolutionary method for analogue integrated circuits diagnosis is presented in this paper. The method allows for global parametric faults localization at the prototype stage of life of an analogue integrated circuit. The presented method is based on the circuit under test response base and the advanced features classification. A classifier is built with the use of evolutionary algorithms, such as differential evolution and gene expression programming. As the proposed diagnosis method might be applied at the production phase there is a method for shortening the diagnosis time suggested. An evolutionary approach has been verified with the use of several exemplary circuits – an oscillator, a band-pass filter and two operational amplifiers. A comparison of the presented algorithm and two classical methods – the linear classifier and the nearest neighborhood method – proves that the heuristic approach allows for acquiring significantly better results.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 1; 133-142
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    GPU-based tuning of quantum-inspired genetic algorithm for a combinatorial optimization problem
    Autorzy:
    Nowotniak, R.
    Kucharski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/201268.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    quantum-inspired genetic algorithm
    evolutionary computing
    meta-optimization
    parallel algorithms
    GPGPU
    Opis:
    This paper concerns efficient parameters tuning (meta-optimization) of a state-of-the-art metaheuristic, Quantum-Inspired Genetic Algorithm (QIGA), in a GPU-based massively parallel computing environment (NVidia CUDATMtechnology). A novel approach to parallel implementation of the algorithm has been presented. In a block of threads, each thread transforms a separate quantum individual or different quantum gene; In each block, a separate experiment with different population is conducted. The computations have been distributed to eight GPU devices, and over 400× speedup has been gained in comparison to Intel Core i7 2.93GHz CPU. This approach allows efficient meta-optimization of the algorithm parameters. Two criteria for the meta-optimization of the rotation angles in quantum genes state space have been considered. Performance comparison has been performed on combinatorial optimization (knapsack problem), and it has been presented that the tuned algorithm is superior to Simple Genetic Algorithm and to original QIGA algorithm.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 2; 323-330
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Multiobjective shape optimization of selected coupled problems by means of evolutionary algorithms
    Autorzy:
    Długosz, A.
    Burczyński, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/202348.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    multiobjective optimization
    evolutionary algorithms
    multiphysics
    coupled field problems
    finite element method
    Opis:
    In present paper an improved multi-objective evolutionary algorithm is used for Pareto optimization of selected coupled problems. Coupling of mechanical, electrical and thermal fields is considered. Boundary-value problems of the thermo-elasticity, piezoelectricity and electro-thermo-elasticity are solved by means of finite element method (FEM). Ansys Multiphysics and MSC.Mentat/Marc software are used to solve considered coupled problems. Suitable interfaces between optimization tool and the FEM software are created. Different types of functionals are formulated on the basis of results obtained from the coupled field analysis. Functionals depending on the area or volume of the structure are also proposed. Parametric curves NURBS are used to model some optimized structures. Numerical examples for exemplary three-objective optimization are presented in the paper.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 2; 215-222
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and finite bit word length
    Autorzy:
    Słowik, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/202324.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial intelligence
    evolutionary algorithms
    digital filters
    minimal phase
    finite bits word length
    Opis:
    In this paper an application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and with finite bit word length is presented. Four digital filters with infinite impulse response were designed using the proposed method. These digital filters possess: linearly falling characteristics, linearly growing characteristics, nonlinearly falling characteristics, and nonlinearly growing characteristics, and they are designed using bit words with an assumed length. This bit word length is connected with a processing register size. This register size depends on hardware possibilities where digital filter is to be implemented. In this paper, a modification of the mutation operator is introduced too. Due to this modification, better results were obtained in relation to the results obtained using the evolutionary algorithm with other mutation operators. The digital filters designed using the proposed method can be directly implemented in the hardware (DSP system) without any additional modifications.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2011, 59, 2; 125-135
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Asymptotic guarantee of success for multi-agent memetic systems
    Autorzy:
    Byrski, A.
    Schaefer, R.
    Smołka, M.
    Cotta, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/201942.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    computational multi-agent systems
    asymptotic analysis
    global optimization
    parallel evolutionary algorithms
    Markov chain modeling
    Opis:
    The paper introduces a stochastic model for a class of population-based global optimization meta-heuristics, that generalizes existing models in the following ways. First of all, an individual becomes an active software agent characterized by the constant genotype and the meme that may change during the optimization process. Second, the model embraces the asynchronous processing of agent’s actions. Third, we consider a vast variety of possible actions that include the conventional mixing operations (e.g. mutation, cloning, crossover) as well as migrations among demes and local optimization methods. Despite the fact that the model fits many popular algorithms and strategies (e.g. genetic algorithms with tournament selection) it is mainly devoted to study memetic algorithms. The model is composed of two parts: EMAS architecture (data structures and management strategies) allowing to define the space of states and the framework for stochastic agent actions and the stationary Markov chain described in terms of this architecture. The probability transition function has been obtained and the Markov kernels for sample actions have been computed. The obtained theoretical results are helpful for studying metaheuristics conforming to the EMAS architecture. The designed synchronization allows the safe, coarse-grained parallel implementation and its effective, sub-optimal scheduling in a distributed computer environment. The proved strong ergodicity of the finite state Markov chain results in the asymptotic stochastic guarantee of success, which in turn imposes the liveness of a studied metaheuristic. The Markov chain delivers the sampling measure at an arbitrary step of computations, which allows further asymptotic studies, e.g. on various kinds of the stochastic convergence.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2013, 61, 1; 257-278
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Genetic minimisation of peak-to-peak level of a complex multi-tone signal
    Autorzy:
    Chruszczyk, Ł.
    Powiązania:
    https://bibliotekanauki.pl/articles/201424.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    evolutionary computation
    genetic algorithms
    multi-tone signal
    optimisation
    peak-to-peak minimisation
    obliczenia ewolucyjne
    algorytmy genetyczne
    sygnał wielotonowy
    optymalizacja
    Opis:
    This paper presents results of evolutionary minimisation of peak-to-peak value of a?multi-tone signal. The signal is the sum of multiple tones (channels) with constant amplitudes and frequencies combined with variable phases. An exemplary application is emergency broadcasting using widely used analogue broadcasting techniques: citizens band (CB) or VHF FM commercial broadcasting. The work presented illustrates a?relatively simple problem, which, however, is characterised by large combinatorial complexity, so direct (exhaustive) search becomes completely impractical. The process of minimisation is based on genetic algorithm (GA), which proves its usability for given problem. The final result is a?significant reduction of peak-to-peak level of given multi-tone signal, demonstrated by three real-life examples.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 3; 621-629
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Recent developments in simulation-driven multi-objective design of antennas
    Autorzy:
    Koziel, S.
    Bekasiewicz, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/201914.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    computer-aided design
    CAD
    antenna design
    multi-objective optimization
    surrogate models
    evolutionary algorithms
    projektowanie wspomagane komputerowo
    projektowanie anteny
    model zastępczy
    algorytmy ewolucyjne
    Opis:
    This paper addresses computationally feasible multi-objective optimization of antenna structures. We review two recent techniques that utilize the multi-objective evolutionary algorithm (MOEA) working with fast antenna replacement models (surrogates) constructed as Kriging interpolation of coarse-discretization electromagnetic (EM) simulation data. The initial set of Pareto-optimal designs is subsequently refined to elevate it to the high-fidelity EM simulation accuracy. In the first method, this is realized point-by-point through appropriate response correction techniques. In the second method, sparsely sampled high-fidelity simulation data is blended into the surrogate model using Co-kriging. Both methods are illustrated using two design examples: an ultra-wideband (UWB) monocone antenna and a planar Yagi-Uda antenna. Advantages and disadvantages of the methods are also discussed.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 3; 781-789
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Handling fuzzy systems’ accuracy-interpretability trade-off by means of multi-objective evolutionary optimization methods – selected problems
    Autorzy:
    Gorzałczany, M. B.
    Rudziński, F.
    Powiązania:
    https://bibliotekanauki.pl/articles/199824.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    accuracy and interpretability of fuzzy rule-based systems
    multi-objective evolutionary optimization
    genetic computations
    fuzzy systems
    dokładność systemów rozmytych
    optymalizacja
    obliczenia genetyczne
    systemy rozmyte
    Opis:
    The paper addresses several open problems regarding the automatic design of fuzzy rule-based systems (FRBSs) from data using multi-objective evolutionary optimization algorithms (MOEOAs). In particular, we propose: a) new complexity-related interpretability measure, b) efficient strong-fuzzy-partition implementation for improving semantics-related interpretability, c) special-coding-free implementation of rule base and original genetic operators for its processing, and d) implementation of our ideas in the context of well-known MOEOAs such as SPEA2 and NSGA-II. The experiments demonstrate that our approach is an effective tool for handling FRBSs’ accuracy-interpretability trade-off, i.e, designing FRBSs characterized by various levels of such a trade-off (in particular, for designing highly interpretability-oriented systems of still competitive accuracy).
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 3; 791-798
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

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