Relevant bibliographies by topics / Hybridní algoritmus

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Academic literature on the topic 'Hybridní algoritmus'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Hybridní algoritmus"

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Kohel, Petr, and Rastislav Toman. "DEVELOPMENT OF A CONTROL ALGORITHM FOR A PARALLEL HYBRID POWERTRAIN." MECCA Journal of Middle European Construction and Design of Cars 17, no. 1 (July 20, 2020): 14. http://dx.doi.org/10.14311/mecdc.2020.01.03.

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The current legislation calls for fast electrification of vehicle powertrains, since it is necessary to fulfil the CO2 requirements for the vehicle fleets. The hybrid electric vehicles (HEV) with parallel powertrain topologies – together with pure battery electric vehicles (BEV) – are the most common ways of electrification. However, the HEV powertrain – opposed to the BEV or conventional powertrain – poses an interesting challenge associated with the control system design to achieve the ideal power split between an internal combustion engine (ICE) and electrical machines (EM) during the whole vehicle operation.The presented paper sums up the specific functions and requirements on a control system, together with the description of general control strategy options for a HEV powertrain. The proposed control strategy then combines heuristic rules with a suboptimal numerical control method, calculating the optimal power split ratio based on the efficiencies of ICE and EMs. This control strategy is built into a modular algorithm in Matlab/Simulink for two different parallel HEV powertrain topologies: P2 and P0P4. It is subsequently coupled with a vehicle models created in GT-Suite environment and tested on a WLTC homologation driving cycles. The following simulation tests show the fuel consumption reduction potential for chosen HEV topologies working in hybrid modes, in comparison to a base operation with conventional mode only. Yet, the heuristic rules can be further optimized to obtain even better overall results.Současná legislativa tlačí výrobce vozidel k okamžité elektrifikaci pohonu, protože je to v tuto chvíli jediná možnost, jak dostát požadavkům na flotilové emise CO2. Nejběžnější formou elektrifikace pohonu jsou v dnešní době vozidla s paralelním hybridním pohonem anebo bateriové elektromobily. Nicméně hybridní pohon, na rozdíl právě od konvenčního nebo čistě elektrického pohonu, představuje zajímavé výzvy spojené s návrhem řídicího algoritmu, který musí v každém okamžiku zajišťovat optimální rozdělení výkonu mezi spalovací motor a elektromotor.Tento článek v úvodu krátce shrnuje specifické funkce a požadavky na takový řídicí algoritmus, společně s obecným přehledem možných řídicích strategií hybridních vozidel. Následně je navržena řídicí strategie kombinující heuristická pravidla se suboptimální numerickou metodou, která vypočítává parametr optimálního dělení výkonu na základě účinností spalovacího motoru a elektromotoru. Na základě navrhnuté strategie je v programu Matlab/Simulink vytvořen modulární řídicí algoritmus pro dvě paralelní hybridní topologie: P2 a P0P4, který je následně propojen s modely vozidel vytvořenými v simulačním prostředí GT-Suite a testován v homologačním cyklu WLTC. Nakonec je prezentováno několik testů řídicího algoritmu, které demonstrují úsporu paliva vybraných topologií hybridního vozidla pracujících v hybridních režimech, ve srovnání s provozem pouze v konvenčním režimu pohonu. Avšak heuristická pravidla mohou být dále optimalizována, s cílem dosáhnout ještě příznivějších celkových výsledků.
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Habbal, Abderrahmane, Lionel Fourment, and Tien Tho Do. "Algorithmes hybrides pour l’optimisation globale." European Journal of Computational Mechanics 17, no. 3 (January 2008): 303–22. http://dx.doi.org/10.3166/remn.17.303-322.

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Kopfer, Herbert, Giselher Pankratz, and Elmar Erkens. "Entwicklung eines hybriden Genetischen Algorithmus zur Tourenplanung." Operations-Research-Spektrum 16, no. 1 (March 1994): 21–31. http://dx.doi.org/10.1007/bf01719700.

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Fleurent, Charles, and Jacques A. Ferland. "Algorithmes génétiques hybrides pour l'optimisation combinatoire." RAIRO - Operations Research 30, no. 4 (1996): 373–98. http://dx.doi.org/10.1051/ro/1996300403731.

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Fieg, G., X. Luo, and B. Oest. "Hybrider genetischer Algorithmus für die Synthese von großskaligen Wärmeübertragernetzwerken." Chemie Ingenieur Technik 81, no. 8 (August 2009): 1119. http://dx.doi.org/10.1002/cite.200950318.

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Robinson, A. Jebamalai, S. C. Punitha S. C. Punitha, and Dr P. Ranjit Jeba Thangaiah. "Hybrid Attribute Selection Process for Decision Tree Based Classification Algorithms." Indian Journal of Applied Research 1, no. 9 (October 1, 2011): 34–36. http://dx.doi.org/10.15373/2249555x/jun2012/14.

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Sawant, Parantapa, Willi Nieratschker, Marc Nadler, and Christian Braasch. "Energetische und ökonomische Analyse von realen dezentralen hybriden Energiesystemen." BWK ENERGIE. 73, no. 7-8 (2021): 61–65. http://dx.doi.org/10.37544/1618-193x-2021-7-8-61.

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Im Rahmen des EU-Forschungsprojektes ACA-Modes (Advanced Control Algorithms for Management of Decentralised Energy Systems) werden reale Labore der Projektpartner primärenergetisch, ökonomisch und die Emissionen betreffend bewertet. Vier Projektpartner liefern Datensätze aus Messreihen typischer Bereitstellungsszenarien. Die verschiedenen Systeme bestehen unter anderem aus einer KWK-Anlage mit Erdgas-Verbrennungsmotor, einer KWKK-Anlage mit Adsorptionskältemaschine, einer Photovoltaik-Anlage mit Batteriespeicher und Wärmepumpe und einer Solarthermieanlage mit Adsorptionskältemaschine.
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Deleau, Hervé, Jin-Kao Hao, and Frédéric Saubion. "Algorithmes hybrides génériques pour la résolution de problèmes de satisfaction de contraintes." RAIRO - Operations Research 39, no. 2 (April 2005): 87–103. http://dx.doi.org/10.1051/ro:2005006.

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Widarma, Adi. "COMBINATION AES, RC4 AND ELGAMAL ALGORITHM IN HYBRID SCHEME FOR DATA SECURITY." Computer Engineering, Science and System Journal 1, no. 1 (January 31, 2016): 1–8. http://dx.doi.org/10.24114/cess.v1i1.4040.

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Haque, Md Enamul, and Talal M. Alkharobi. "Adaptive Hybrid Model for Network Intrusion Detection and Comparison among Machine Learning Algorithms." International Journal of Machine Learning and Computing 5, no. 1 (February 2015): 17–23. http://dx.doi.org/10.7763/ijmlc.2015.v5.476.

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Dissertations / Theses on the topic "Hybridní algoritmus"

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Stacha, Radek. "Optimalizace kogeneračního systému." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-231502.

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Master thesis is focused on optimization of cogeneration system for purpose of rating optimization methods and evaluating properties of these methods. For each method there is description together with block schemes. First part of thesis is devoted to description of methods and their comparison. Second part consists of development of hybrid algorithm, which is used to optimize cogeneration systém model. Each algorithm compared is together with hybrid algorithms included in annexes.
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Hrabec, Dušan. "Mathematical Programs for Dynamic Pricing - Demand Based Management." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-263401.

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Tato disertační práce se zabývá vývojem, modelováním a analýzou poptávkově orientovaných úloh, které zahrnují marketingová, operační a logistická rozhodnutí. Úlohy jsou zvoleny tak, aby mohly být dále rozšířeny o koncept tzv. dynamického oceňování a jiných dynamických marketingových rozhodnutí. V práci jsou využity dvě základní poptávkově orientované úlohy: a) úloha kolportéra novin, která je zvolena pro její jednoduchou formu a která tak slouží jako nástroj pro ilustrativní ukázky rozhodovacích procesů v podobných typech úloh, a b) úloha návrhu dopravní sítě, kde jsou využity některé výsledky a znalosti získané při řešení úlohy kolportéra novin. Kolportér (či obecně maloobchodník) čelí náhodné poptávce, která může být postupně ovlivněna oceňováním, marketingovými (tj. reklamními) rozhodnutími a nakonec jejich kombinací. Poptávka obsahuje tedy náhodnou složku, která je pomocí přístupů stochastické optimalizace modelována ve specifickém tvaru (tj. aditivní či multiplikativní tvar). Závislost cena-poptávka je zachycena pomocí nelineární klesající poptávkové funkce, zatímco (vhodná) reklama vede ke zvýšení poptávky (běžně rostoucí s-křivka či konkávní funkce). Výsledky získané při řešení úlohy kolportéra novin s oceňováním jsou následně využity v úloze návrhu dopravní sítě. Tato stochastická úloha je modelována (reformulována) pomocí dvou přístupů stochastické optimalizace: wait-and-see přístup a here-and-now přístup. Jelikož tato implementace vede na lineární či nelineární celočíselnou (navíc scénářovou) úlohu, jsou v práci zmíněny taky výpočetní nástroje. Autor pro řešení používá (původní) tzv. hybridní algoritmus, což je kombinace heuristického (genetického) algoritmu a nástroje optimalizačního softwaru. Potenciální aplikace sestavených modelů, obzvláště v oblasti odpadového hospodářství, jsou diskutovány v závěrečné části disertační práce.
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Šandera, Čeněk. "Hybridní model metaheuristických algoritmů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-234259.

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The main topic of this PhD thesis is metaheuristic algorithm in wider scope. The first chapters are dedicated to a description of broader context of metaheuristics, i.e. various optimization classes, determination of their omplexity and different approaches to their solutions. The consequent discussion about metaheuristics and their typical characteristics is followed by several selected examples of metaheuristics concepts. The observed characteristics serve as a base for building general metaheuristics model which is suitable for developing brand new or hybrid algorithms. The thesis is concluded by illustration of author’s publications with discussion about their adaptation to the proposed model. On the attached CD, there is also available a program implementation of the created model.
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Hachimi, Hanaa. "Hybridations d'algorithmes métaheuristiques en optimisation globale et leurs applications." Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00905604.

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L'optimisation des structures est un processus essentiel dans la conception des systèmes mécaniques et électroniques. Cette thèse s'intéresse à la résolution des problèmes mono-objectifs et multi-objectifs des structures mécaniques et mécatroniques. En effet, les industriels ne sont pas seulement préoccupés à améliorer les performances mécaniques des pièces qu'ils conçoivent, mais ils cherchent aussi à optimiser leurs poids, leurs tailles, ainsi que leurs coûts de production. Pour résoudre ce type de problème, nous avons fait appel à des métaheuristiques robustes qui nous permettent de minimiser le coût de production de la structure mécanique et de maximiser le cycle de vie de la structure. Alors que des méthodes inappropriées de l'évolution sont plus difficiles à appliquer à des modèles mécaniques complexes en raison de temps calcul exponentiel. Il est connu que les algorithmes génétiques sont très efficaces pour les problèmes NP-difficiles, mais ils sont très lourds et trop gourmands quant au temps de calcul, d'où l'idée d'hybridation de notre algorithme génétique par l'algorithme d'optimisation par essaim de particules (PSO) qui est plus rapide par rapport à l'algorithme génétique (GA). Dans notre expérimentation, nous avons obtenu une amélioration de la fonction objectif et aussi une grande amélioration de la minimisation de temps de calcul. Cependant, notre hybridation est une idée originale, car elle est différente des travaux existants. Concernant l'avantage de l'hybridation, il s'agit généralement de trois méthodes : l'hybridation en série, l'hybridation en parallèle et l'hybridation par insertion. Nous avons opté pour l'hybridation par insertion par ce qu'elle est nouvelle et efficace. En effet, les algorithmes génétiques se composent de trois étapes principales : la sélection, le croisement et la mutation. Dans notre cas, nous remplaçons les opérateurs de mutation par l'optimisation par essaim de particules. Le but de cette hybridation est de réduire le temps de calcul ainsi que l'amélioration la solution optimale.
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Horáková, Pavla. "Optimalizace pro registraci obrazů založená na genetických algoritmech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219505.

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Diploma thesis is focused on global optimization methods and their utilization for medical image registration. The main aim is creation of the genetic algorithm and test its functionality on synthetic data. Besides test functions and test figures algorithm was subjected to real medical images. For this purpose was created graphical user interface with choise of parameters according to actual requirement. After adding an iterative gradient method it became of hybrid genetic algorithm.
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Naldi, Murilo Coelho. "Agrupamento híbrido de dados utilizando algoritmos genéticos." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-07112006-080351/.

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Técnicas de Agrupamento vêm obtendo bons resultados quando utilizados em diversos problemas de análise de dados, como, por exemplo, a análise de dados de expressão gênica. Porém, uma mesma técnica de agrupamento utilizada em um mesmo conjunto de dados pode resultar em diferentes formas de agrupar esses dados, devido aos possíveis agrupamentos iniciais ou à utilização de diferentes valores para seus parâmetros livres. Assim, a obtenção de um bom agrupamento pode ser visto como um processo de otimização. Esse processo procura escolher bons agrupamentos iniciais e encontrar o melhor conjunto de valores para os parâmetros livres. Por serem métodos de busca global, Algoritmos Genéticos podem ser utilizados durante esse processo de otimização. O objetivo desse projeto de pesquisa é investigar a utilização de Técnicas de Agrupamento em conjunto com Algoritmos Genéticos para aprimorar a qualidade dos grupos encontrados por algoritmos de agrupamento, principalmente o k-médias. Esta investigação será realizada utilizando como aplicação a análise de dados de expressão gênica. Essa dissertação de mestrado apresenta uma revisão bibliográfica sobre os temas abordados no projeto, a descrição da metodologia utilizada, seu desenvolvimento e uma análise dos resultados obtidos.
Clustering techniques have been obtaining good results when used in several data analysis problems, like, for example, gene expression data analysis. However, the same clustering technique used for the same data set can result in different ways of clustering the data, due to the possible initial clustering or the use of different values for the free parameters. Thus, the obtainment of a good clustering can be seen as an optimization process. This process tries to obtain good clustering by selecting the best values for the free parameters. For being global search methods, Genetic Algorithms have been successfully used during the optimization process. The goal of this research project is to investigate the use of clustering techniques together with Genetic Algorithms to improve the quality of the clusters found by clustering algorithms, mainly the k-means. This investigation was carried out using as application the analysis of gene expression data, a Bioinformatics problem. This dissertation presents a bibliographic review of the issues covered in the project, the description of the methodology followed, its development and an analysis of the results obtained.
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Gomes, Wellison José de Santana. "Estudo do efeito de incertezas na otimização estrutural." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/18/18134/tde-23032010-092000/.

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Este trabalho apresenta um estudo do efeito de incertezas na otimização estrutural. Tal efeito pode ser quantificado em termos de probabilidades de falha bem como do risco, ou custo esperado de falha. O estudo se baseia na comparação dos resultados obtidos através de três distintas formulações do problema de otimização estrutural: otimização determinística, otimização baseada em confiabilidade e otimização de risco estrutural. Para efeitos de comparação, informações sobre risco de falha estrutural (produto da probabilidade de falha pelo custo de falha) são incorporadas nas três formulações. A otimização determinística (DDO - Deterministic Design Optimization) permite encontrar uma configuração estrutural que é ótima em termos mecânicos, mas não considera explicitamente a incerteza dos parâmetros e seus efeitos na segurança estrutural. Em conseqüência, a segurança da estrutura ótima pode ser comprometida, em comparação à segurança da estrutura original. A otimização baseada em confiabilidade (RBDO - Reliability-Based Design Optimization) garante que a estrutura ótima mantenha um nível mínimo (e mensurável) de segurança. Entretanto, os resultados são dependentes da probabilidade de falha usada como restrição na análise. A otimização de risco estrutural (RBRO - Reliability-Based Risk Optimization) aumenta o escopo do problema, buscando um balanço entre economia e segurança, objetivos estes que de uma forma geral competem entre si. Isto é possível através da quantificação de custos associados à construção, operação e manutenção da estrutura, bem como das consequências monetárias de falha. A experiência mostra que problemas de otimização estudados, são utilizados neste trabalho dois métodos de otimização heurísticos: algoritmos genéticos e método do enxame de partículas. Tendo a eficiência como objetivo, dois métodos com fundamentação matemática também são estudados: os métodos de Powell e de Polak-Ribiere. Finalmente, buscando uma relação de compromisso entre confiabilidade (capacidade de encontrar o mínimo global em todos os problemas) e eficiência, quatro algoritmos híbridos são construídos, combinando os quatro métodos citados anteriormente. Efeitos de incertezas na otimização estrutural são estudados através da comparação de soluções obtidas via diferentes formulações do problema de otimização. São apresentados alguns estudos de caso, enfatizando as diferenças entre os projetos ótimos obtidos por cada formulação. O estudo mostra que, em geral, a estrutura ótima só é encontrada pela formulação mais abrangente: a otimização de risco ou RBRO. O estudo mostra que, para que a formulação DDO encontre a mesma configuração ótima da formulação RBRO, é necessário especificar um coeficiente de segurança ótimo para cada modo de falha. De maneira semelhante, o estudo mostra que quando os custos associados a diferentes modos de falha são distintos, a formulação RBDO somente resulta na estrutura ótima quando uma probabilidade de falha ótima é especificada como restrição para cada modo falha da estrutura.
In this study the effects of uncertainty on optimum structural design are investigated, by comparing three distinct formulations of a structural optimization problem. Such effects can be quantified in terms of failure probabilities and risk, or expected costs of failure. Deterministic Design Optimization (DDO) allows one the find the shape or configuration of a structure that is optimum in terms of mechanics, but the formulation do not consider explicitly parameter uncertainty and its effects on structural safety. As a consequence, safety of the optimum structure can be compromised, in comparison to safety of the original structure. Reliability-based Design Optimization (RBDO) has emerged as an alternative to properly model the safety-under-uncertainty part of the problem. With RBDO, one can ensure that a minimum (and measurable) level of safety is achieved by the optimum structure. However, results are dependent on the failure probability used as constraint in the analysis. Risk optimization increases the scope of the problem, by addressing the compromising goals of economy and safety, and allowing one to find a proper point of balance between these goals. This is accomplished by quantifying the costs associated to construction, operation and maintenance of the structure, as well as the monetary consequences of failure. Experience shows that structural optimization problems can have multiple local minima. With the objective of finding the global minimum in all studied problems, two heuristic optimization methods are used in this study: genetic algorithms and particle swarm optimization. Aiming at efficiency, two methods with mathematical foundations are also considered: the methods of Powel and Polak-Ribiere. Finally, looking for a compromise between reliability (capacity to find the global minimum) and efficiency, four hybrid algorithms are constructed, combining the four methods just cited. The study investigates the effects of uncertainty on optimum structural design by comparing solutions obtained via the different formulations of the optimization problem. The paper presents some case studies, highlighting the differences in the optimum designs obtained with each formulation. The study leads to a better understanding of the limitations of each formulation in the solution of structural optimization problems. The investigation shows that, in general, the optimum structure can only be found by the most comprehensive formulation: risk optimization or RBRO. The study shows that DDO only leads to the optimum structure if an optimum safety coefficient is used as constraint for each individual failure mode. In a similar way, the investigation shows that when the costs associated to distinct failure modes are different, the RBDO formulation only leads to the optimum structural design if an optimum failure probability is specified as constraint for each failure mode of the structure.
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Rebreyend, Pascal. "Algorithmes génétiques hybrides en optimisation combinatoire." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 1999. http://tel.archives-ouvertes.fr/tel-00010950.

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Cette thèse aborde le problème de la résolution des problèmes combinatoires à l'aide d'algorithmes génétiques. Ce type d'algorithme présente en effet nombres d'avantages. Cependant, ils sont généralement relativement lents. Cette thèse est donc centrée sur les algorithmes hybrides, c'est-à-dire des algorithmes construits à l'aide de plusieurs méthodes différentes. Dans notre cas, nous étudions les algorithmes qui réunissent algorithmes génétiques et heuristiques. Il existe deux méthodes pour générer de tels algorithmes qui sont la représentation directe et la représentation indirecte. Ces deux méthodes sont étudiés au travers de trois problèmes distincts : l'ordonnancement statique de programmes parallèles, le placement de composants électroniques et la planification de réseaux cellulaires. Pour chacun des trois problèmes, les algorithmes hybrides ont montrés leur efficacité. Pour le problème de la planification de réseaux cellulaires, une nouvelle modélisation a été faite. Cette modélisation permet d'effectuer en même temps le placement des émetteurs et l'allocation de fréquences.
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Rebreyend, Pascal. "Algorithmes genetiques hybrides en optimisation combinatoire." Lyon, École normale supérieure (sciences), 1999. http://www.theses.fr/1999ENSL0108.

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Cette these porte sur les problemes d'optimisation combinatoire et sur leur resolution grace aux algorithmes genetiques, notamment ceux hybrides. Cette these traite les trois problemes suivants : l'ordonnancement de programmes paralleles, le placement de composants sur circuits imprimes et la construction de reseaux de telephonie cellulaire. Ces problemes sont resolus par l'utilisation d'algorithmes genetiques hybrides. Les algorithmes genetiques sont une methode interessante et facilement parallelisable pour trouver une solution sous-optimale d'un probleme combinatoire. Ils sont bases sur la theorie de l'evolution des especes. Leur methode consiste donc a faire evoluer une population d'individus ou de solutions. Cette these examine et compare les deux principales facons de coupler un algorithme genetique avec une heuristique. Ces deux methodes sont nommees representation directe et representation indirecte. Dans le cas de la representation directe, l'heuristique est introduite au sein de l'algorithme genetique en modifiant les operateurs de croisement ou de mutation. La representation indirecte consiste a utiliser l'algorithme genetique pour determiner un ordre total sur les elements du probleme. On utilise alors une heuristique ou algorithme de liste qui construit la solution pas a pas en tenant compte de cet ordre. A part le probleme de l'ordonnancement, cette these presente et explique la modelisation de chaque probleme, modelisation qui est necessaire afin de pouvoir exploiter au mieux les caracteristiques des algorithmes genetiques. Les trois problemes etudies ont permis d'experimenter les deux types d'algorithmes genetiques hybrides. Les algorithmes hybrides testes ont montre leur efficacite par rapport aux heuristiques classiques. Les resultats obtenus confirment l'interet d'adapter l'algorithme genetique au probleme traite.
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Vladimir, Lončar. "Hybrid parallel algorithms for solving nonlinear Schrödinger equation." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2017. https://www.cris.uns.ac.rs/record.jsf?recordId=104931&source=NDLTD&language=en.

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Numerical methods and algorithms for solving of partial differential equations, especially parallel algorithms, are an important research topic, given the very broad applicability range in all areas of science. Rapid advances of computer technology open up new possibilities for development of faster algorithms and numerical simulations of higher resolution. This is achieved through paralleliza-tion at different levels that  practically all current computers support.In this thesis we develop parallel algorithms for solving one kind of partial differential equations known as nonlinear Schrödinger equation (NLSE) with a convolution integral kernel. Equations of this type arise in many fields of physics such as nonlinear optics, plasma physics and physics of ultracold atoms, as well as economics and quantitative  finance. We focus on a special type of NLSE, the dipolar Gross-Pitaevskii equation (GPE), which characterizes the behavior of ultracold atoms in the state of Bose-Einstein condensation.We present novel parallel algorithms for numerically solving GPE for a wide range of modern parallel computing platforms, from shared memory systems and dedicated hardware accelerators in the form of graphics processing units (GPUs), to   heterogeneous computer clusters. For shared memory systems, we provide an algorithm and implementation targeting multi-core processors us-ing OpenMP. We also extend the algorithm to GPUs using CUDA toolkit and combine the OpenMP and CUDA approaches into a hybrid, heterogeneous al-gorithm that is capable of utilizing all  available resources on a single computer. Given the inherent memory limitation a single  computer has, we develop a distributed memory algorithm based on Message Passing Interface (MPI) and previous shared memory approaches. To maximize the performance of hybrid implementations, we optimize the parameters governing the distribution of data  and workload using a genetic algorithm. Visualization of the increased volume of output data, enabled by the efficiency of newly developed algorithms, represents a challenge in itself. To address this, we integrate the implementations with the state-of-the-art visualization tool (VisIt), and use it to study two use-cases which demonstrate how the developed programs can be applied to simulate real-world systems.
Numerički metodi i algoritmi za rešavanje parcijalnih diferencijalnih jednačina, naročito paralelni algoritmi, predstavljaju izuzetno značajnu oblast istraživanja, uzimajući u obzir veoma široku primenljivost u svim oblastima nauke. Veliki napredak informacione tehnologije otvara nove mogućnosti za razvoj bržih al-goritama i  numeričkih simulacija visoke rezolucije. Ovo se ostvaruje kroz para-lelizaciju na različitim nivoima koju poseduju praktično svi moderni računari. U ovoj tezi razvijeni su paralelni algoritmi za rešavanje jedne vrste parcijalnih diferencijalnih jednačina poznate kao nelinearna Šredingerova jednačina sa inte-gralnim konvolucionim kernelom. Jednačine ovog tipa se javljaju u raznim oblas-tima fizike poput nelinearne optike, fizike plazme i fizike ultrahladnih atoma, kao i u ekonomiji i kvantitativnim finansijama. Teza se bavi posebnim oblikom nelinearne Šredingerove jednačine, Gros-Pitaevski jednačinom sa dipol-dipol in-terakcionim članom, koja karakteriše ponašanje ultrahladnih atoma u stanju Boze-Ajnštajn kondenzacije.U tezi su predstavljeni novi paralelni algoritmi za numeričko rešavanje Gros-Pitaevski jednačine za širok spektar modernih računarskih platformi, od sis-tema sa deljenom memorijom i specijalizovanih hardverskih akceleratora u ob-liku grafičkih procesora, do heterogenih računarskih klastera. Za sisteme sa deljenom memorijom, razvijen je  algoritam i implementacija namenjena više-jezgarnim centralnim procesorima  korišćenjem OpenMP tehnologije. Ovaj al-goritam je proširen tako da radi i u  okruženju grafičkih procesora korišćenjem CUDA alata, a takođe je razvijen i  predstavljen hibridni, heterogeni algoritam koji kombinuje OpenMP i CUDA pristupe i koji je u stanju da iskoristi sve raspoložive resurse jednog računara.Imajući u vidu inherentna ograničenja raspoložive memorije koju pojedinačan računar poseduje, razvijen je i algoritam za sisteme sa distribuiranom memorijom zasnovan na Message Passing Interface tehnologiji i prethodnim algoritmima za sisteme sa deljenom memorijom. Da bi se maksimalizovale performanse razvijenih hibridnih implementacija, parametri koji određuju raspodelu podataka i računskog opterećenja su optimizovani korišćenjem genetskog algoritma. Poseban izazov je vizualizacija povećane količine izlaznih podataka, koji nastaju kao rezultat efikasnosti novorazvijenih algoritama. Ovo je u tezi rešeno kroz inte-graciju implementacija sa najsavremenijim alatom za vizualizaciju (VisIt), što je omogućilo proučavanje dva primera koji pokazuju kako razvijeni programi mogu da se iskoriste za simulacije realnih sistema.
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Books on the topic "Hybridní algoritmus"

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Abraham, Ajith, Crina Grosan, and Hisao Ishibuchi, eds. Hybrid Evolutionary Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6.

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Affenzeller, Michael. New hybrid variants of genetic algorithms: Theoretical and practical aspects. Linz: Universitätsverlag Rudolf Trauner, 2003.

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Affenzeller, Michael. New hybrid variants of genetic algorithms: Theoretical and practical aspects. Linz: Universitätsverlag Rudolf Trauner, 2003.

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Neural, novel & hybrid algorithms for time series prediction. New York: John Wiley & Sons, 1995.

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Moursli, Omar. Scheduling the hybrid flowshop: Branch and bound algorithms. Louvain-la-Neuve: CIACO, 1999.

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Oliva, Diego, and Salvador Hinojosa, eds. Applications of Hybrid Metaheuristic Algorithms for Image Processing. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40977-7.

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Lincoln, Patrick. A formally verified alrgothim for interactive consistency under a hybrid fault model. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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Lincoln, Patrick. A formally verified alrgothim for interactive consistency under a hybrid fault model. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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Hallett, Andrew Hughes. Hybrid algorithms with automatic switching for solving nonlinear equation systems. Glasgow: Dept. of Economics, Fraser of Allander Institute, University of Strathclyde, 1996.

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Ruan, Da. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms. Boston, MA: Springer US, 1997.

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Book chapters on the topic "Hybridní algoritmus"

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Ošmera, Pavel, and Jan Roupec. "Integrated Evolutionary Algorithms." In Hybrid Information Systems, 353–59. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1782-9_26.

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Lee, Taito, Shuhei Denzumi, and Kunihiko Sadakane. "Engineering Hybrid DenseZDDs." In Experimental Algorithms, 201–16. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38851-9_14.

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Grosan, Crina, and Ajith Abraham. "Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews." In Hybrid Evolutionary Algorithms, 1–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_1.

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Hoque, Md T., M. Chetty, and L. S. Dooley. "Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction." In Hybrid Evolutionary Algorithms, 241–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_10.

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Xhafa, F. "A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids." In Hybrid Evolutionary Algorithms, 269–311. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_11.

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Hruschka, E. R., L. N. de Castro, and R. J. G. B. Campello. "Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search." In Hybrid Evolutionary Algorithms, 313–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_12.

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Calderon, F., J. J. Flores, and L. Romero. "Robust Parametric Image Registration." In Hybrid Evolutionary Algorithms, 337–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_13.

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Kumar, R., and P. K. Singh. "Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP." In Hybrid Evolutionary Algorithms, 361–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_14.

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da Cruz, A. V. Abs, M. M. B. R. Vellasco, and M. A. C. Pacheco. "Quantum-Inspired Evolutionary Algorithm for Numerical Optimization." In Hybrid Evolutionary Algorithms, 19–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_2.

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Dellino, G., P. Lino, C. Meloni, and A. Rizzo. "Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective." In Hybrid Evolutionary Algorithms, 39–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73297-6_3.

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Conference papers on the topic "Hybridní algoritmus"

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Szu, Harold. "Iterative Restoration Algorithms For Nonlinear Constraint Computing." In Optical and Hybrid Computing, edited by Harold H. Szu. SPIE, 1986. http://dx.doi.org/10.1117/12.964007.

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Kasparis, Takis, George Eichmann, Michael Georgiopoulos, and Gregory L. Heileman. "Image pattern algorithms using neural networks." In Hybrid Image and Signal Processing II, edited by David P. Casasent and Andrew G. Tescher. SPIE, 1990. http://dx.doi.org/10.1117/12.21323.

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Islam, Md, and Christian Rothenberg. "HAS Based Empirical QoE Study over TCP and QUIC on Diverse Networks." In Workshop Pré-IETF. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/wpietf.2020.13794.

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HTTP adaptive streaming (HAS) is the de-facto standard for video services over the Internet delivering increased Quality of Experience (QoE) as a function of the network status. Such adaptive streaming atop HTTP relies predominantly on TCP as the reliable transport protocol. Recently, QUIC, an alternative of TCP transport, has emerged to overcome TCP’s native shortcomings and improve the HTTP-based applications QoE. This paper investigates three strategies (Rate, Buffer, and Hybrid) based adaptive bitrate streaming (ABS) algorithms behavioral performance over the traditional TCP and QUIC transport protocol. For this purpose, we experimentally evaluate different cellular network traces in a high-fidelity emulated testbed and compare the performance of ABS algorithms considering QoE metrics over TCP and QUIC. Our empirical results show that each ABS algorithm’s (Conventional, BBA, and Arbiter) QoE performance is biased for TCP. As a result, QUIC suffers the ineffectiveness of traditional state-of-art ABS algorithms to improve video streaming performance without specific changes.
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Li, Rui, Bir Bhanu, and Krzysztof Krawiec. "Hybrid coevolutionary algorithms vs. SVM algorithms." In the 9th annual conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1276958.1277057.

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Pargas, Roy P., Jennifer Ludwick, and Steven Spoon. "Hybrid search algorithms." In the 1997 ACM symposium. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/331697.331752.

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Tragha, A., F. Omary, and A. Mouloudi. "ICIGA: Improved Cryptography Inspired by Genetic Algorithms." In 2006 International Conference on Hybrid Information Technology. IEEE, 2006. http://dx.doi.org/10.1109/ichit.2006.253509.

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Yang, Cheng-San, Li-Yeh Chuang, Yu-Jung Chen, and Cheng-Hong Yang. "Feature Selection Using Memetic Algorithms." In 2008 Third International Conference on Convergence and Hybrid Information Technology (ICCIT). IEEE, 2008. http://dx.doi.org/10.1109/iccit.2008.81.

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Gao, Sicun. "Session details: Algorithms and Foundations." In HSCC '18: 21st International Conference on Hybrid Systems: Computation and Control. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3258031.

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Zelnio, Edmund G., Theresa Scarnati, and Benjamin Lewis. "Hybrid neural net template-based ATR (Conference Presentation)." In Algorithms for Synthetic Aperture Radar Imagery XXVI, edited by Edmund Zelnio and Frederick D. Garber. SPIE, 2019. http://dx.doi.org/10.1117/12.2523436.

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Park, Joon-Sang, Won W. Ro, Handuck Lee, and Neungsoo Park. "Parallel Algorithms for Steiner Tree Problem." In 2008 Third International Conference on Convergence and Hybrid Information Technology (ICCIT). IEEE, 2008. http://dx.doi.org/10.1109/iccit.2008.167.

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Reports on the topic "Hybridní algoritmus"

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Lemmon, Michael D., and Panos J. Antsaklis. Fast Algorithms for Hybrid Control System Design. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada344941.

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Karniadakis, George E. High-Order Algorithms for 3D Plasma Simulations on Unstructured and Hybrid Meshes. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada381671.

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Kohavi, Ronny, and Nils J. Nilsson. Final Technical Report for Hybrid Algorithms and Oblivious Decision Graphs Using MLC++. Fort Belvoir, VA: Defense Technical Information Center, February 1996. http://dx.doi.org/10.21236/ada327585.

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Abdel-Khalik, Hany S., and Qiong Zhang. Development of Subspace-based Hybrid Monte Carlo-Deterministric Algorithms for Reactor Physics Calculations. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1154733.

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