Informacja

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

Wyszukujesz frazę "genetic optimization algorithm" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Genetic and combinatorial algorithms for optimal sizing and placement of active power filters
Autorzy:
Maciążek, M.
Grabowski, D.
Pasko, M.
Powiązania:
https://bibliotekanauki.pl/articles/330809.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
power quality
optimization
active power filter
harmonics
genetic algorithm
combinatorial algorithm
jakość energii
energetyczny filtr aktywny
algorytm genetyczny
algorytm kombinatoryczny
Opis:
The paper deals with cost effective compensator placement and sizing. It becomes one of the most important problems in contemporary electrical networks, in which voltage and current waveform distortions increase year-by-year reaching or even exceeding limit values. The suppression of distortions could be carried out by means of three types of compensators, i.e., passive filters, active power filters and hybrid filters. So far, passive filters have been more popular mainly because of economic reasons, but active and hybrid filters have some advantages which should cause their wider application in the near future. Active power filter placement and sizing could be regarded as an optimization problem. A few objective functions have been proposed for this problem. In this paper we compare solutions obtained by means of combinatorial and genetic approaches. The theoretical discussion is followed by examples of active power filter placement and sizing.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 2; 269-279
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A factor graph based genetic algorithm
Autorzy:
Helmi, B. H.
Rahmani, A. T.
Pelikan, M.
Powiązania:
https://bibliotekanauki.pl/articles/330811.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
optimization problem
genetic algorithm
estimation
distribution algorithm
factor graph
matrix factorization
problem optymalizacji
algorytm genetyczny
algorytm estymacji rozkładu
faktoryzacja macierzy
Opis:
We propose a new linkage learning genetic algorithm called the Factor Graph based Genetic Algorithm (FGGA). In the FGGA, a factor graph is used to encode the underlying dependencies between variables of the problem. In order to learn the factor graph from a population of potential solutions, a symmetric non-negative matrix factorization is employed to factorize the matrix of pair-wise dependencies. To show the performance of the FGGA, encouraging experimental results on different separable problems are provided as support for the mathematical analysis of the approach. The experiments show that FGGA is capable of learning linkages and solving the optimization problems in polynomial time with a polynomial number of evaluations.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 3; 621-633
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid approach for scheduling transportation networks
Autorzy:
Dridi, M.
Kacem, I.
Powiązania:
https://bibliotekanauki.pl/articles/907640.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
system transportowy
regulacja ruchu
algorytm genetyczny
optymalizacja wielokryterialna
transportation systems
traffic regulation
genetic algorithm
multicriteria optimization
Opis:
In this paper, we consider a regulation problem of an urban transportation network. From a given timetable, we aim to find a new schedule of multiple vehicles after the detection of a disturbance at a given time. The main objective is to find a solution maximizing the level of service for all passengers. This problem was intensively studied with evolutionary approaches and multi-agent techniques, but without identifying its type before. In this paper, we formulate the problem as a classical one in the case of an unlimited vehicle capacity. In the case of a limited capacity and an integrity constraint, the problem becomes difficult to solve. Then, a new coding and well-adapted operators are proposed for such a problem and integrated in a new evolutionary approach.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2004, 14, 3; 397-409
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decentralized job scheduling in the cloud based on a spatially generalized Prisoner’s Dilemma game
Autorzy:
Gąsior, J.
Seredyński, F.
Powiązania:
https://bibliotekanauki.pl/articles/329736.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
job scheduling
multiobjective optimization
genetic algorithm
prisoner's dilemma
cellular automata
harmonogramowanie zadań
optymalizacja wielokryterialna
algorytm genetyczny
dylemat więźnia
automat komórkowy
Opis:
We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 4; 737-751
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

    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