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Wyszukujesz frazę "meta-optimization" wg kryterium: Temat

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    Wyświetlanie 1-8 z 8
    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:
    Optimal point to point path planning of flexible manipulator under large deformation by using harmony search method
    Autorzy:
    Esfandiar, H.
    Korayem, M. H.
    Powiązania:
    https://bibliotekanauki.pl/articles/280605.pdf
    Data publikacji:
    2016
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    meta-heuristic optimization
    harmony search
    large deformation
    flexible manipulator
    Opis:
    This paper aims at planning an optimal point to point path for a flexible manipulator under large deformation. For this purpose, the researchers use a direct method and meta-heuristic optimization process. In this paper, the maximum load carried by the manipulator and the minimum transmission time are taken as objective functions of the optimization process to get optimal path profiles. Kinematic constraints, the maximum velocity and acceleration, the dynamic constraint of the maximum torque applied to the arms and also the constraint of final point accuracy are discussed. For the optimization process, the Harmony Search (HS) method is used. To evaluate the effectiveness of the approach proposed, simulation studies are reviewed by considering a two-link flexible manipulator with the fixed base. The findings indicate that the proposed method is in power of dealing with nonlinear dynamics of the system. Furthermore, the results obtained by rigid, small and large deformation models are compared with each other.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2016, 54, 1; 179-193
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An efficient parallel global optimization strategy based on Kriging properties suitable for material parameters identification
    Autorzy:
    Roux, Emile
    Tillier, Yannick
    Kraria, Salim
    Bouchard, Pierre-Olivier
    Powiązania:
    https://bibliotekanauki.pl/articles/140296.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    global optimization
    parallel computation
    Kriging meta-model
    inverse analysis
    Opis:
    Material parameters identification by inverse analysis using finite element computations leads to the resolution of complex and time-consuming optimization problems. One way to deal with these complex problems is to use meta-models to limit the number of objective function computations. In this paper, the Efficient Global Optimization (EGO) algorithm is used. The EGO algorithm is applied to specific objective functions, which are representative of material parameters identification issues. Isotropic and anisotropic correlation functions are tested. For anisotropic correlation functions, it leads to a significant reduction of the computation time. Besides, they appear to be a good way to deal with the weak sensitivity of the parameters. In order to decrease the computation time, a parallel strategy is defined. It relies on a virtual enrichment of the meta-model, in order to compute q new objective functions in a parallel environment. Different methods of choosing the qnew objective functions are presented and compared. Speed-up tests show that Kriging Believer (KB) and minimum Constant Liar (CLmin) enrichments are suitable methods for this parallel EGO (EGO-p) algorithm. However, it must be noted that the most interesting speed-ups are observed for a small number of objective functions computed in parallel. Finally, the algorithm is successfully tested on a real parameters identification problem.
    Źródło:
    Archive of Mechanical Engineering; 2020, LXVII, 2; 169-195
    0004-0738
    Pojawia się w:
    Archive of Mechanical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Metaheuristic optimization of marginal risk constrained long - short portfolios
    Autorzy:
    Vijayalakshmi Pai, G. A.
    Michel, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/91858.pdf
    Data publikacji:
    2012
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    metaheuristic
    optimization
    portfolio optimization
    marginal risk
    quadratic programming
    meta heuristic method
    data envelopment analysis
    Opis:
    The problem of portfolio optimization with its twin objectives of maximizing expected portfolio return and minimizing portfolio risk renders itself difficult for direct solving using traditional methods when constraints reflective of investor preferences, risk management and market conditions are imposed on the underlying mathematical model. Marginal risk that represents the risk contributed by an asset to the total portfolio risk is an important criterion during portfolio selection and risk management. However, the inclusion of the constraint turns the problem model into a notorious non-convex quadratic constrained quadratic programming problem that seeks acceptable solutions using metaheuristic methods. In this work, two metaheuristic methods, viz., Evolution Strategy with Hall of Fame and Differential Evolution (rand/1/bin) with Hall of Fame have been evolved to solve the complex problem and compare the quality of the solutions obtained. The experimental studies have been undertaken on the Bombay Stock Exchange (BSE200) data set for the period March 1999-March 2009. The efficiency of the portfolios obtained by the two metaheuristic methods have been analyzed using Data Envelopment Analysis.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 3; 259-274
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Modified blind naked mole-rat algorithm applied to electromagnetic design problems
    Autorzy:
    Taherdangkoo, Mohammad
    Powiązania:
    https://bibliotekanauki.pl/articles/1841273.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    electromagnetic design problems
    global optimization
    meta-heuristic algorithm
    problemy z projektowaniem elektromagnetycznym
    globalna optymalizacja
    algorytm metaheurystyczny
    Opis:
    In this paper,we proposed a modified meta-heuristic algorithm based on the blind naked mole-rat (BNMR) algorithm to solve the multiple standard benchmark problems. We then apply the proposed algorithm to solve an engineering inverse problem in the electromagnetic field to validate the results. The main objective is to modify the BNMR algorithm by employing two different types of distribution processes to improve the search strategy. Furthermore, we proposed an improvement scheme for the objective function and we have changed some parameters in the implementation of the BNMR algorithm. The performance of the BNMR algorithm was improved by introducing several new parameters to find the better target resources in the implementation of a modified BNMR algorithm. The results demonstrate that the changed candidate solutions fall into the neighborhood of the real solution. The results show the superiority of the propose method over other methods in solving various mathematical and electromagnetic problems.
    Źródło:
    Archives of Electrical Engineering; 2021, 70, 2; 167-380
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A novel variant of the salp swarm algorithm for engineering optimization
    Autorzy:
    Jia, Fuyun
    Luo, Sheng
    Yin, Guan
    Ye, Yin
    Powiązania:
    https://bibliotekanauki.pl/articles/23944824.pdf
    Data publikacji:
    2023
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    salp swarm algorithm
    meta-heuristic algorithm
    chaos theory
    sine-cosine mechanism
    quantum computation
    optimization design of engineering
    Opis:
    There are many design problems need to be optimized in various fields of engineering, and most of them belong to the NP-hard problem. The meta-heuristic algorithm is one kind of optimization method and provides an effective way to solve the NP-hard problem. Salp swarm algorithm (SSA) is a nature-inspired algorithm that mimics and mathematically models the behavior of slap swarm in nature. However, similar to most of the meta-heuristic algorithms, the traditional SSA has some shortcomings, such as entrapment in local optima. In this paper, the three main strategies are adopted to strengthen the basic SSA, including chaos theory, sine-cosine mechanism and the principle of quantum computation. Therefore, the SSA variant is proposed in this research, namely SCQ-SSA. The representative benchmark functions are employed to test the performances of the algorithms. The SCQ-SSA are compared with the seven algorithms in high-dimensional functions (1000 dimensions), seven SSA variants and six advanced variants on benchmark functions, the experiment reveals that the SCQ-SSA enhances resulting precision and alleviates local optimal problems. Besides, the SCQ-SSA is applied to resolve three classical engineering problems: tubular column design problem, tension/compression spring design problem and pressure vessel design problem. The design results indicate that these engineering problems are optimized with high accuracy and superiority by the improved SSA. The source code is available in the URL: https://github.com/ye-zero/SCQSSA/tree/main/SCQ-SSA.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 131--149
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robustness of Support Vector Machines in Algorithmic Trading on Cryptocurrency Market
    Autorzy:
    Ślepaczuk, Robert
    Zenkova, Maryna
    Powiązania:
    https://bibliotekanauki.pl/articles/1356913.pdf
    Data publikacji:
    2019-08-07
    Wydawca:
    Uniwersytet Warszawski. Wydział Nauk Ekonomicznych
    Tematy:
    Machine learning
    support vector machines
    investment algorithm
    algorithmic trading
    strategy
    optimization
    cross-validation
    overfitting
    cryptocurrency market
    technical analysis
    meta parameters
    Opis:
    This study investigates the profitability of an algorithmic trading strategy based on training SVM model to identify cryptocurrencies with high or low predicted returns. A tail set is defined to be a group of coins whose volatility-adjusted returns are in the highest or the lowest quintile. Each cryptocurrency is represented by a set of six technical features. SVM is trained on historical tail sets and tested on the current data. The classifier is chosen to be a nonlinear support vector machine. The portfolio is formed by ranking coins using the SVM output. The highest ranked coins are used for long positions to be included in the portfolio for one reallocation period. The following metrics were used to estimate the portfolio profitability: %ARC (the annualized rate of change), %ASD (the annualized standard deviation of daily returns), MDD (the maximum drawdown coefficient), IR1, IR2 (the information ratio coefficients). The performance of the SVM portfolio is compared to the performance of the four benchmark strategies based on the values of the information ratio coefficient IR1, which quantifies the risk-weighted gain. The question of how sensitive the portfolio performance is to the parameters set in the SVM model is also addressed in this study.
    Źródło:
    Central European Economic Journal; 2018, 5, 52; 186 - 205
    2543-6821
    Pojawia się w:
    Central European Economic Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Solving scheduling problems with integrated online sustainability observation using heuristic optimization
    Autorzy:
    Burduk, Anna
    Musiał, Kamil
    Balashov, Artem
    Batako, Andre
    Safonyk, Andrii
    Powiązania:
    https://bibliotekanauki.pl/articles/2173719.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    production scheduling
    sustainable development
    genetic algorithm
    meta-heuristics
    intelligent optimization methods of production systems
    tabu search
    harmonogramowanie produkcji
    zrównoważony rozwój
    algorytm genetyczny
    przeszukiwanie tabu
    metaheurystyki
    inteligentne metody optymalizacji systemów produkcyjnych
    Opis:
    The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143830
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

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