Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "evolutionary algorithms" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-8 z 8
    Tytuł:
    Evolutionary algorithms for job-shop scheduling
    Autorzy:
    Mesghouni, K.
    Hammadi, S.
    Borne, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/907245.pdf
    Data publikacji:
    2004
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    harmonogramowanie produkcji
    algorytm ewolucyjny
    reprezentacja równoległa
    job-shop scheduling
    evolutionary algorithms
    parallel representation
    Opis:
    This paper explains how to use Evolutionary Algorithms (EA) to deal with a flexible job shop scheduling problem, especially minimizing the makespan. The Job-shop Scheduling Problem (JSP) is one of the most difficult problems, as it is classified as an NP-complete one (Carlier and Chretienne, 1988; Garey and Johnson, 1979). In many cases, the combination of goals and resources exponentially increases the search space, and thus the generation of consistently good scheduling is particularly difficult because we have a very large combinatorial search space and precedence constraints between operations. Exact methods such as the branch and bound method and dynamic programming take considerable computing time if an optimum solution exists. In order to overcome this difficulty, it is more sensible to obtain a good solution near the optimal one. Stochastic search techniques such as evolutionary algorithms can be used to find a good solution. They have been successfully used in combinatorial optimization, e.g. in wire routing, transportation problems, scheduling problems, etc. (Banzhaf et al., 1998; Dasgupta and Michalewicz, 1997). Our objective is to establish a practical relationship between the development in the EA area and the reality of a production JSP by developing, on the one hand, two effective genetic encodings, such as parallel job and parallel machine representations of the chromosome, and on the other, genetic operators associated with these representations. In this article we deal with the problem of flexible job-shop scheduling which presents two difficulties: the first is the assignment of each operation to a machine, and the other is the scheduling of this set of operations in order to minimize our criterion (e.g. the makespan).
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2004, 14, 1; 91-103
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Advances in model-based fault diagnosis with evolutionary algorithms and neural networks
    Autorzy:
    Witczak, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/908460.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    diagnostyka uszkodzeń
    algorytmy ewolucyjne
    sieci neuronowe
    odporność
    fault diagnosis
    evolutionary algorithms
    neural networks
    robustness
    Opis:
    Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as evolutionary algorithms and neural networks become more and more popular in industrial applications of fault diagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionary algorithms and neural networks to fault diagnosis. In particular, a brief introduction to these computational intelligence paradigms is presented, and then a review of their fault detection and isolation applications is performed. Close attention is paid to techniques that integrate the classical and soft computing methods. A selected group of them is carefully described in the paper. The performance of the presented approaches is illustrated with the use of the DAMADICS fault detection benchmark that deals with a valve actuator.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 1; 85-99
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Phenotypic evolution with a mutation based on symmetric alpha-stable distributions
    Autorzy:
    Obuchowicz, A.
    Prętki, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/907644.pdf
    Data publikacji:
    2004
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    algorytm ewolucyjny
    dystrybucja stabilna
    optymalizacja globalna
    evolutionary algorithms
    Levy-stable distributions
    global optimization
    surrounding effect
    Opis:
    Multidimensional Symmetric alpha-Stable (S alpha S) mutations are applied to phenotypic evolutionary algorithms. Such mutations are characterized by non-spherical symmetry for alpha<2 and the fact that the most probable distance of mutated points is not in a close neighborhood of the origin, but at a certain distance from it. It is the so-called surrounding effect (Obuchowicz, 2001b; 2003b). For alpha=2, the S alpha S mutation reduces to the Gaussian one, and in the case of alpha=1, the Cauchy mutation is obtained. The exploration and exploitation abilities of evolutionary algorithms, using S alpha S mutations for different alpha, are analyzed by a set of simulation experiments. The obtained results prove the important influence of the surrounding effect of symmetric alpha-stable mutations on both the abilities considered.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2004, 14, 3; 289-316
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Customized crossover in evolutionary sets of safe ship trajectories
    Autorzy:
    Szłapczyński, R.
    Szłapczyńska, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/331257.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    algorytm ewolucyjny
    unikanie kolizji statków
    system wspomagania decyzji
    evolutionary algorithms
    ship collision avoidance
    decision support systems
    Opis:
    The paper presents selected aspects of evolutionary sets of safe ship trajectories-a method which applies evolutionary algorithms and some of the assumptions of game theory to solving ship encounter situations. For given positions and motion parameters of the ships, the method finds a near optimal set of safe trajectories of all ships involved in an encounter. The method works in real time and the solutions must be returned within one minute, which enforces speeding up the optimisation process. During the development of the method the authors tested various problem-dedicated crossover operators to obtain the best performance. The results of that research are given here. The paper includes a detailed description of these operators as well as statistical simulation results and examples of experiment results.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 4; 999-1009
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The island model as a Markov dynamic system
    Autorzy:
    Schaefer, R.
    Byrski, A.
    Smołka, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/331253.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    algorytm genetyczny
    analiza asymptotyczna
    optymalizacja globalna
    algorytm ewolucyjny równoległy
    łańcuch Markova
    genetic algorithms
    asymptotic analysis
    global optimization
    parallel evolutionary algorithms
    Markov chain modeling
    Opis:
    Parallel multi-deme genetic algorithms are especially advantageous because they allow reducing the time of computations and can perform a much broader search than single-population ones. However, their formal analysis does not seem to have been studied exhaustively enough. In this paper we propose a mathematical framework describing a wide class of island-like strategies as a stationary Markov chain. Our approach uses extensively the modeling principles introduced by Vose, Rudolph and their collaborators. An original and crucial feature of the framework we propose is the mechanism of inter-deme agent operation synchronization. It is important from both a practical and a theoretical point of view. We show that under a mild assumption the resulting Markov chain is ergodic and the sequence of the related sampling measures converges to some invariant measure. The asymptotic guarantee of success is also obtained as a simple issue of ergodicity. Moreover, if the cardinality of each island population grows to infinity, then the sequence of the limit invariant measures contains a weakly convergent subsequence. The formal description of the island model obtained for the case of solving a single-objective problem can also be extended to the multi-objective case.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 4; 971-984
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    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:
    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:
    Niching mechanisms in evolutionary computations
    Autorzy:
    Kowalczuk, Z.
    Białaszewski, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/908461.pdf
    Data publikacji:
    2006
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    algorytm genetyczny
    projektowanie inżynierskie
    obliczenia ewolucyjne
    obserwator detekcyjny
    niching
    ranking
    Pareto optimality
    genetic algorithms
    evolutionary computations
    multi-objective optimisation
    solutions diversity
    engineering designs
    detection observers
    Opis:
    Different types of niching can be used in genetic algorithms (GAs) or evolutionary computations (ECs) to sustain the diversity of the sought optimal solutions and to increase the effectiveness of evolutionary multi-objective optimization solvers. In this paper four schemes of niching are proposed, which are also considered in two versions with respect to the method of invoking: a continuous realization and a periodic one. The characteristics of these mechanisms are discussed, while as their performance and effectiveness are analyzed by considering exemplary multi-objective optimization tasks both of a synthetic and an engineering (FDI) design nature.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2006, 16, 1; 59-84
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-8 z 8

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies