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    Wyświetlanie 1-14 z 14
    Tytuł:
    Memetic algorithm for assembly sequence planning
    Autorzy:
    Jankowski, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/1429342.pdf
    Data publikacji:
    2008
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    evolutionary computing
    assembly
    optimisation
    process planning
    Opis:
    The paper presents the application of a memetic algorithm to searching for the optimal sequence of the assembly of parts. Such approach is based on the use of an algorithm connecting two methods of global and local search in order to increase the effectiveness of the conducted optimisation process. Based on a proper representation of assembly sequences and a set of geometrical, topological and technological constraints, connected with the attributes of a product, it is possible to create an evolutionary model. Through proper control of the evolution process in a model, based on the appropriate selection of parameters, it is possible to achieve good results in a short period of time. Although the evolutionary algorithm does not guarantee the obtaining of optimal solutions, it has been proven, based on sample simulations, that such solutions are obtained in a repeated manner. The application of the presented evolutionary approach enables creating fast assembly sequence planning tools, indispensable in tactical planning and operational control of manufacturing processes.
    Źródło:
    Journal of Machine Engineering; 2008, 8, 3; 77-90
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fine tuning of agent-based evolutionary computing
    Autorzy:
    Mizera, Michal
    Nowotarski, Pawel
    Byrski, Aleksander
    Kisiel-Dorohinicki, Marek
    Powiązania:
    https://bibliotekanauki.pl/articles/91820.pdf
    Data publikacji:
    2019
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    multi-agent systems
    metaheuristics
    evolutionary computing
    Opis:
    Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 2; 81-97
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Evolutionary approach to ship’s trajectory planning within Traffic Separation Schemes
    Autorzy:
    Szłapczyński, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/259049.pdf
    Data publikacji:
    2012
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    marine navigation
    Traffic Separation Schemes
    collision avoidance manoeuvres
    evolutionary computing
    Opis:
    The paper presents the continuation of the author’s research on evolutionary approach to ship trajectory planning. While the general problem of the evolutionary trajectory planning has already been solved, no one has yet touched one of its specific aspects: evolutionary trajectory planning within Traffic Separation Schemes. Traffic Separation Scheme (TSS) is a traffic-management route-system complying with rules of the International Maritime Organization. In brief, the ships navigating within a TSS all sail in the direction assigned to a particular traffic lane or they cross at a course angle as close to 90 degrees as possible. This and other TSS rules largely affect the evolutionary method. The paper presents a proposal of the extended evolutionary method, with a focus on changes that have to be made to obey TSS rules, especially the changes in the phases of evaluation and specialised operators of the evolutionary cycle.
    Źródło:
    Polish Maritime Research; 2012, 1; 11-20
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    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:
    Evolutionary computation based on Bayesian classifiers
    Autorzy:
    Miquelez, T.
    Bengoetxea, E.
    Larranaga, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/907630.pdf
    Data publikacji:
    2004
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    rozumowanie probabilistyczne
    obliczenia ewolucyjne
    sieć Bayesa
    estymacja algorytmu dystrybucji
    hybrid soft computing
    probabilistic reasoning
    evolutionary computing
    classification
    optimization
    Bayesian networks
    estimation of distribution algorithms
    Opis:
    Evolutionary computation is a discipline that has been emerging for at least 40 or 50 years. All methods within this discipline are characterized by maintaining a set of possible solutions (individuals) to make them successively evolve to fitter solutions generation after generation. Examples of evolutionary computation paradigms are the broadly known Genetic Algorithms (GAs) and Estimation of Distribution Algorithms (EDAs). This paper contributes to the further development of this discipline by introducing a new evolutionary computation method based on the learning and later simulation of a Bayesian classifier in every generation. In the method we propose, at each iteration the selected group of individuals of the population is divided into different classes depending on their respective fitness value. Afterwards, a Bayesian classifier---either naive Bayes, seminaive Bayes, tree augmented naive Bayes or a similar one---is learned to model the corresponding supervised classification problem. The simulation of the latter Bayesian classifier provides individuals that form the next generation. Experimental results are presented to compare the performance of this new method with different types of EDAs and GAs. The problems chosen for this purpose are combinatorial optimization problems which are commonly used in the literature.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2004, 14, 3; 335-349
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Artificial Immune System Approach for Smart Air-Conditioning Control
    Autorzy:
    Chaczko, Z.
    Aslanzadeh, S.
    Kuleff, J. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/227264.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    artificial immune system
    biologically inspired computing
    evolutionary computation
    Opis:
    Biologically inspired computing that looks to nature and biology for inspiration is a revolutionary change to our thinking about solving complex computational problems. It looks into nature and biology for inspiration rather than conventional approaches. The Human Immune System with its complex structure and the capability of performing pattern recognition, self-learning, immune-memory, generation of diversity, noise tolerance, variability, distributed detection and optimisation - is one area that has been of strong interest and inspiration for the last decade. An air conditioning system is one example where immune principles can be applied. This paper describes new computational technique called Artificial Immune System that is based on immune principles and refined for solving engineering problems. The presented system solution applies AIS algorithms to monitor environmental variables in order to determine how best to reach the desired temperature, learn usage patterns and predict usage needs. The aim of this paper is to explore the AIS-based artificial intelligence approach and its impact on energy efficiency. It will examine, if AIS algorithms can be integrated within a Smart Air Conditioning System as well as analyse the impact of such a solution.
    Źródło:
    International Journal of Electronics and Telecommunications; 2012, 58, 2; 193-199
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An Analytical Study for the Role of Fuzzy Logic in Improving Metaheuristic Optimization Algorithms
    Autorzy:
    Vij, Sonakshi
    Jain, Amita
    Tayal, Devendra
    Castillo, Oscar
    Powiązania:
    https://bibliotekanauki.pl/articles/385121.pdf
    Data publikacji:
    2018
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    fuzzy logic
    metaheuristics
    evolutionary computing
    genetic algorithm
    particle swarm optimization (PSO)
    ant colony optimization
    fuzzy evolutionary algorithm
    fuzzy cuckoo
    fuzzy simulated annealing
    fuzzy swarm intelligence
    fuzzy differential evolution
    tabu
    fuzzy mutation
    fuzzy natural selection
    fuzzy fitness function
    big bang big crunch
    fuzzy bacterial
    neuro fuzzy logic
    logika rozmyta
    metaheurystyka
    obliczenia ewolucyjne
    algorytm genetyczny
    optymalizacja roju cząstek
    optymalizacja kolonii mrówek
    Opis:
    The research applications of fuzzy logic have always been multidisciplinary in nature due to its ability in handling vagueness and imprecision. This paper presents an analytical study in the role of fuzzy logic in the area of metaheuristics using Web of Science (WoS) as the data source. In this case, 178 research papers are extracted from it in the time span of 1989-2016. This paper analyzes various aspects of a research publication in a scientometric manner. The top cited research papers, country wise contribution, topmost organizations, top research areas, top source titles, control terms and WoS categories are analyzed. Also, the top 3 fuzzy evolutionary algorithms are extracted and their top research papers are mentioned along with their topmost research domain. Since neuro fuzzy logic poses feasible options for solving numerous research problems, hence a section is also included by the authors to present an analytical study regarding research in it. Overall, this study helps in evaluating the recent research patterns in the field of fuzzy metaheuristics along with envisioning the future trends for the same. While on one hand this helps in providing a new path to the researchers who are beginners in this field as they can start exploring it through the analysis mentioned here, on the other hand it provides an insight to professional researchers too who can dig a little deeper in this field using knowledge from this study.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 4; 11-27
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Learning board evaluation function for Othello by hybridizing coevolution with temporal difference learning
    Autorzy:
    Szubert, M.
    Jaśkowski, W.
    Krawiec, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/206175.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    evolutionary computation
    coevolutionary algorithms
    reinforcement learning
    memetic computing
    game strategy learning
    Opis:
    Hybridization of global and local search techniques has already produced promising results in the fields of optimization and machine learning. It is commonly presumed that approaches employing this idea, like memetic algorithms combining evolutionary algorithms and local search, benefit from complementarity of constituent methods and maintain the right balance between exploration and exploitation of the search space. While such extensions of evolutionary algorithms have been intensively studied, hybrids of local search with coevolutionary algorithms have not received much attention. In this paper we attempt to fill this gap by presenting Coevolutionary Temporal Difference Learning (CTDL) that works by interlacing global search provided by competitive coevolution and local search by means of temporal difference learning. We verify CTDL by applying it to the board game of Othello, where it learns board evaluation functions represented by a linear architecture of weighted piece counter. The results of a computational experiment show CTDL superiority compared to coevolutionary algorithm and temporal difference learning alone, both in terms of performance of elaborated strategies and computational cost. To further exploit CTDL potential, we extend it by an archive that keeps track of selected well-performing solutions found so far and uses them to improve search convergence. The overall conclusion is that the fusion of various forms of coevolution with a gradient-based local search can be highly beneficial and deserves further study.
    Źródło:
    Control and Cybernetics; 2011, 40, 3; 805-831
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO
    Autorzy:
    Nagaraj, B.
    Vijayakumar, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/384767.pdf
    Data publikacji:
    2011
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    ant colony algorithm
    evolutionary program
    genetic algorithm particle swarm optimization and soft computing
    Opis:
    Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 2; 42-48
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parallel and distributed implementation of optimization algorithms in fe analyses
    Implementacja optymalizacyjnych algorytmów równoległych i rozproszonych w analizie MES
    Autorzy:
    Handrik, M.
    Vasko, M.
    Kopas, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/196393.pdf
    Data publikacji:
    2012
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    FEM analysis
    optimization
    parallel computing
    distributed computing
    BOINC
    grid computing
    evolutionary algorithms
    analiza MES
    optymalizacja
    obliczenia równoległe
    obliczenia rozproszone
    rozproszony model obliczeniowy
    algorytm ewolucyjny
    Opis:
    The aim of this paper is analysis of optimization algorithms in terms of their possible solutions in parallelization and distributed computing systems. Main goal is using of evolutionary algorithms and implementation of parallel algorithms. As the software platform for application of distributed optimization algorithms is using software package BOINC. For evaluation of the objective function is used FEM program ADINA.
    Artykuł analizuje algorytmy optymalizacyjne pod kątem ich możliwości obliczeń równoległych oraz rozproszonych systemów obliczeniowych. Ukierunkowany jest przede wszystkim na algorytmy ewolucyjne oraz ich implementację równoległą. Jako platforma softwarowa do zastosowania rozproszonego systemu obliczeniowego algorytmu zostało zastosowane oprogramowanie pośredniczące BOINC. W celu oceny funkcji docelowej został zastosowany w MES program ADINA.
    Źródło:
    Zeszyty Naukowe. Transport / Politechnika Śląska; 2012, 76; 67-74
    0209-3324
    2450-1549
    Pojawia się w:
    Zeszyty Naukowe. Transport / Politechnika Śląska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems
    Autorzy:
    Chmaj, G.
    Walkowiak, K.
    Tarnawski, M.
    Kucharzak, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/330970.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    system obliczeniowy P2P
    przetwarzanie rozproszone
    optymalizacja
    heurystyka
    algorytm ewolucyjny
    P2P computing system
    distributed computing
    optimization
    heuristics
    evolutionary algorithms
    Opis:
    Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very close to an optimum and can be used for larger problem instances than those solvable by CPLEX or other ILP solvers.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 3; 733-748
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An efficient approach for view selection for data warehouse using tree mining and evolutionary computation
    Autorzy:
    Thakare, A.
    Deshpande, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/305413.pdf
    Data publikacji:
    2018
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    database management systems
    data warehousing and data mining
    query optimization
    graph mining
    algorithms for parallel computing
    evolutionary computations
    genetic algorithms
    Opis:
    The selection of a proper set of views to materialize plays an important role in database performance. There are many methods of view selection that use different techniques and frameworks to select an efficient set of views for materialization. In this paper, we present a new efficient scalable method for view selection under the given storage constraints using a tree mining approach and evolutionary optimization. The tree mining algorithm is designed to determine the exact frequency of (sub)queries in the historical SQL dataset. The Query Cost model achieves the objective of maximizing the performance benefits from the final view set that is derived from the frequent view set given by the tree mining algorithm. The performance benefit of a query is defined as a function of query frequency, query creation cost, and query maintenance cost. The experimental results show that the proposed method is successful in recommending a solution that is fairly close to an optimal solution.
    Źródło:
    Computer Science; 2018, 19 (4); 431-455
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Approximation of phenol concentration using novel hybrid computational intelligence methods
    Autorzy:
    Pławiak, P.
    Tadeusiewicz, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/907935.pdf
    Data publikacji:
    2014
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    soft computing
    neural network
    genetic algorithm
    fuzzy system
    evolutionary neural system
    pattern recognition
    chemometrics
    przetwarzanie miękkie
    sieć neuronowa
    algorytm genetyczny
    system rozmyty
    rozpoznawanie obrazu
    chemometria
    Opis:
    This paper presents two innovative evolutionary-neural systems based on feed-forward and recurrent neural networks used for quantitative analysis. These systems have been applied for approximation of phenol concentration. Their performance was compared against the conventional methods of artificial intelligence (artificial neural networks, fuzzy logic and genetic algorithms). The proposed systems are a combination of data preprocessing methods, genetic algorithms and the Levenberg–Marquardt (LM) algorithm used for learning feed forward and recurrent neural networks. The initial weights and biases of neural networks chosen by the use of a genetic algorithm are then tuned with an LM algorithm. The evaluation is made on the basis of accuracy and complexity criteria. The main advantage of proposed systems is the elimination of random selection of the network weights and biases, resulting in increased efficiency of the systems.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2014, 24, 1; 165-181
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Collectively intelligent prediction in evolutionary multi-agent system
    Autorzy:
    Kijak, J.
    Martyna, P.
    Byrski, A.
    Faber, Ł.
    Piętak, K.
    Kisiel-Dorohinicki, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/397728.pdf
    Data publikacji:
    2017
    Wydawca:
    Politechnika Łódzka. Wydział Mikroelektroniki i Informatyki
    Tematy:
    evolutionary neural networks
    agent-based computing
    time series prediction
    collective intelligence
    metaheuristic optimization
    ewolucyjne sieci neuronowe
    obliczenia agentowe
    predykcja szeregów czasowych
    inteligencja zbiorowa
    optymalizacja metaheurystyczna
    Opis:
    In the paper a summary of our previously realized and published work connected with constructing collective intelligent evolutionary multi-agent systems for time series prediction, based on multi-layered perceptrons is shown. Besides recalling our past papers, we describe the whole concept, present an implementation in a contemporary, componentoriented software framework AgE 3.0 and we conduct a number of experiments, finding different optimal parametrization for the considered instances of the problems (popular Mackey-Glass chaotic time series). The paper may be useful for a practitioner willing to use our meatheuristic algorithm (EMAS) along with the idea of collective agent-based system in order to realize prediction tasks.
    Źródło:
    International Journal of Microelectronics and Computer Science; 2017, 8, 3; 85-96
    2080-8755
    2353-9607
    Pojawia się w:
    International Journal of Microelectronics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-14 z 14

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