Academic literature on the topic 'Nelder-Mead algoritmus'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Nelder-Mead algoritmus.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Nelder-Mead algoritmus"
1
Lewis, Andrew, David Abramson, and Tom Peachey. "RSCS: A Parallel Simplex Algorithm for the Nimrod/O Optimization Toolset." Scientific Programming 14, no. 1 (2006): 1–11. http://dx.doi.org/10.1155/2006/906394.
Full textAbstract:
This paper describes a method of parallelisation of the popular Nelder-Mead simplex optimization algorithms that can lead to enhanced performance on parallel and distributed computing resources. A reducing set of simplex vertices are used to derive search directions generally closely aligned with the local gradient. When tested on a range of problems drawn from real-world applications in science and engineering, this reducing set concurrent simplex (RSCS) variant of the Nelder-Mead algorithm compared favourably with the original algorithm, and also with the inherently parallel multidirectional search algorithm (MDS). All algorithms were implemented and tested in a general-purpose, grid-enabled optimization toolset.
2
Kshirsagar, Rohit, Steve Jones, Jonathan Lawrence, and Jim Tabor. "Optimization of TIG Welding Parameters Using a Hybrid Nelder Mead-Evolutionary Algorithms Method." Journal of Manufacturing and Materials Processing 4, no. 1 (February 10, 2020): 10. http://dx.doi.org/10.3390/jmmp4010010.
Full textAbstract:
A number of evolutionary algorithms such as genetic algorithms, simulated annealing, particle swarm optimization, etc., have been used by researchers in order to optimize different manufacturing processes. In many cases these algorithms are either incapable of reaching global minimum or the time and computational effort (function evaluations) required makes the application of these algorithms impractical. However, if the Nelder Mead optimization method is applied to approximate solutions cheaply obtained from these algorithms, the solution can be further refined to obtain near global minimum of a given error function within only a few additional function evaluations. The initial solutions (vertices) required for the application of Nelder-Mead optimization can be obtained through multiple evolutionary algorithms. The results obtained using this hybrid method are better than that obtained from individual algorithms and also show a significant reduction in the computation effort.
3
Pošík, Petr, and Waltraud Huyer. "Restarted Local Search Algorithms for Continuous Black Box Optimization." Evolutionary Computation 20, no. 4 (December 2012): 575–607. http://dx.doi.org/10.1162/evco_a_00087.
Full textAbstract:
Several local search algorithms for real-valued domains (axis parallel line search, Nelder-Mead simplex search, Rosenbrock's algorithm, quasi-Newton method, NEWUOA, and VXQR) are described and thoroughly compared in this article, embedding them in a multi-start method. Their comparison aims (1) to help the researchers from the evolutionary community to choose the right opponent for their algorithm (to choose an opponent that would constitute a hard-to-beat baseline algorithm), (2) to describe individual features of these algorithms and show how they influence the algorithm on different problems, and (3) to provide inspiration for the hybridization of evolutionary algorithms with these local optimizers. The recently proposed Comparing Continuous Optimizers (COCO) methodology was adopted as the basis for the comparison. The results show that in low dimensional spaces, the old method of Nelder and Mead is still the most successful among those compared, while in spaces of higher dimensions, it is better to choose an algorithm based on quadratic modeling, such as NEWUOA or a quasi-Newton method.
4
Ali, Ahmed F., and Mohamed A. Tawhid. "Direct Gravitational Search Algorithm for Global Optimisation Problems." East Asian Journal on Applied Mathematics 6, no. 3 (July 20, 2016): 290–313. http://dx.doi.org/10.4208/eajam.030915.210416a.
Full textAbstract:
AbstractA gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed to the Nelder-Mead method to refine it and avoid running iterations that provide negligible further improvement. We test the DGSA on 7 benchmark integer functions and 10 benchmark minimax functions to compare the performance against 9 other algorithms, and the numerical results show the optimal or near optimal solution is obtained faster.
5
Kumar K, Pavan, Murali Mohan J, and Srikanth D. "Generalized solution for inverse kinematics problem of a robot using hybrid genetic algorithms." International Journal of Engineering & Technology 7, no. 4.6 (September 25, 2018): 250. http://dx.doi.org/10.14419/ijet.v7i4.6.20486.
Full textAbstract:
The robot control consists of kinematic control and dynamic control. Control methods of the robot involve forward kinematics and inverse kinematics (IK). In Inverse kinematics the joint angles are found for a given position and orientation of the end effector. Inverse kinematics is a nonlinear problem and has multiple solutions. This computation is required to control the robot arms. A Genetic Algorithm (GA) and Hybrid genetic algorithm (HGA) (Genetic Algorithm in conjunction with Nelder-Mead technique) are proposed for solving the inverse kinematics of a robotic arm. HGA introduces two concepts exploration, exploitation. In an exploration phase, the GA identifies the good areas in entire search space and then exploitation phase is performed inside these areas by using Nelder- mead technique Binary Simulated Crossover and niching strategy for binary tournament selection operator is used. Proposed algorithms can be used on any type of manipulator and the only requirement is the forward kinematic equations, which are easily obtained. As a case study inverse kinematics of a Two Link Elbow Manipulator and PUMA manipulator are solved using GA and HGA in MATLAB. The algorithm is able to find all solutions without any error
6
Papliński, Janusz P. "Hybrid Genetic and Nelder-Mead Algorithms for Identification of Time Delays." IFAC Proceedings Volumes 42, no. 13 (2009): 443–48. http://dx.doi.org/10.3182/20090819-3-pl-3002.00077.
Full text
7
Ahandani, Morteza Alinia, and Hosein Alavi-Rad. "Hybridizing Shuffled Frog Leaping and Shuffled Complex Evolution Algorithms Using Local Search Methods." International Journal of Applied Evolutionary Computation 5, no. 1 (January 2014): 30–51. http://dx.doi.org/10.4018/ijaec.2014010103.
Full textAbstract:
In this research, a study was carried out to exploit the hybrid schemes combining two classical local search techniques i.e. Nelder–Mead simplex search method and bidirectional random optimization with two meta-heuristic methods i.e. the shuffled frog leaping and the shuffled complex evolution, respectively. In this hybrid methodology, each subset of meta-heuristic algorithms is improved by a hybrid strategy that is combined from evolutionary process of each subset in related algorithm and a local search method. These hybrid algorithms are evaluated on low and high dimensional continuous benchmark functions and the obtained results are compared with their non-hybrid competitors. The obtained results demonstrate that the hybrid algorithm combined from shuffled frog leaping and Nelder–Mead simplex has a better success rate but a higher number of function evaluations on low-dimensional functions than the shuffled frog leaping. Whereas on high-dimensional functions it has a better success rate and a faster performance. Also the hybrid algorithm combined from shuffled complex evolution and bidirectional random optimization obtains a better performance in terms of success rate and function evaluations than shuffled complex evolution on low dimensional functions; whereas on high-dimensional functions, it obtains a better success rate but a slower performance. Also a comparison of our hybrid algorithms with the other evolutionary algorithms reported in the literature confirms our proposed algorithms have the best performance among all compared algorithms.
8
Santhosh, M., and P. Sudhakar. "Nelder Mead with Grasshopper Optimization Algorithm for Node Localization in Wireless Sensor Networks." Journal of Computational and Theoretical Nanoscience 17, no. 12 (December 1, 2020): 5409–21. http://dx.doi.org/10.1166/jctn.2020.9434.
Full textAbstract:
Node localization in wireless sensor network (WSN) becomes essential to calculate the coordinate points of the unknown nodes with the use of known or anchor nodes. The efficiency of the WSN has significant impact on localization accuracy. Node localization can be considered as an optimization problem and bioinspired algorithms finds useful to solve it. This paper introduces a novel Nelder Mead with Grasshopper Optimization Algorithm (NMGOA) for node localization in WSN. The Nelder-Mead simplex search method is employed to improve the effectiveness of GOA because of its capability of faster convergence. At the beginning, the nodes in WSN are arbitrarily placed in the target area and then nodes are initialized. Afterwards, the node executes the NMGOA technique for estimating the location of the unknown nodes and become localized nodes. In the subsequent round, the localized nodes will be included to the collection of anchor nodes to perform the localization process. The effectiveness of the NMGOA model is validated using a series of experiments and results indicated that the NMGOA model has achieved superior results over the compared methods.
9
Negrin, Iván A., Alejandro Negrin, and Ernesto L. Chagoyén. "Optimización de pórticos planos de hormigón armado utilizando una hibridación de algoritmos genéticos y el algoritmo Nelder-Mead." Obras y proyectos, no. 26 (December 2019): 74–86. http://dx.doi.org/10.4067/s0718-28132019000200074.
Full text
10
Kriauzienė, Rima, Andrej Bugajev, and Raimondas Čiegis. "A THREE-LEVEL PARALLELISATION SCHEME AND APPLICATION TO THE NELDER-MEAD ALGORITHM." Mathematical Modelling and Analysis 25, no. 4 (October 13, 2020): 584–607. http://dx.doi.org/10.3846/mma.2020.12139.
Full textAbstract:
We consider a three-level parallelisation scheme. The second and third levels define a classical two-level parallelisation scheme and some load balancing algorithm is used to distribute tasks among processes. It is well-known that for many applications the efficiency of parallel algorithms of these two levels starts to drop down after some critical parallelisation degree is reached. This weakness of the twolevel template is addressed by introduction of one additional parallelisation level. s an alternative to the basic solver some new or modified algorithms are considered on this level. The idea of the proposed methodology is to increase the parallelisation degree by using possibly less efficient algorithms in comparison with the basic solver. As an example we investigate two modified Nelder-Mead methods. For the selected application, a Schro¨dinger equation is solved numerically on the second level, and on the third level the parallel Wang’s algorithm is used to solve systems of linear equations with tridiagonal matrices. A greedy workload balancing heuristic is proposed, which is oriented to the case of a large number of available processors. The complexity estimates of the computational tasks are model-based, i.e. they use empirical computational data.
Dissertations / Theses on the topic "Nelder-Mead algoritmus"
1
Hnízdilová, Bohdana. "Registrace ultrazvukových sekvencí s využitím evolučních algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442502.
Full textAbstract:
This master´s thesis deals with the registration of ultrasound sequences using evolutionary algorithms. The theoretical part of the thesis describes the process of image registration and its optimalization using genetic and metaheuristic algorithms. The thesis also presents problems that may occur during the registration of ultrasonographic images and various approaches to their registration. In the practical part of the work, several optimization methods for the registration of a number of sequences were implemented and compared.
2
Hůlka, Tomáš. "Stabilizace chaosu: metody a aplikace." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-320103.
Full textAbstract:
This thesis focuses on deterministic chaos and selected methods of chaos control. It briefly describes the matter of deterministic chaos and presents commonly used tools of analysis of dynamical systems exhibiting chaotic behavior. A list of frequently studied chaotic systems is presented and followed by a description of methods of chaos control and the optimization of these methods. The practical part is dedicated to the stabilization of two model systems and one real system with described methods.
3
Sedláčková, Eva. "Vlnkový wienerovský filtr EKG signálů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220843.
Full textAbstract:
The aim of this work is introduction with method of filtering the ECG signals using wavelet transformation and use of this method for filtering of signal disturbed with myopotencials. The work deals with general properties and with genesis of ECG signals and describes ECG curve. Next part of work is focused on wavelet transformation, types of wavelet transformation and different methods calculation thresholds and thresholding. Design part of work is focused on design Wiener filter for remove myopotencials from ECG signals and finding optimal parameters of this filter using optimization algorithm. For optimization is used simplex method. Discovered optimal parameters are assessed on CSE and MIT-BIH Arrhythmia database and compared with results of other authors.
4
Nhamage, Idilson António. "Aperfeiçoamento do algoritmo de otimização híbrido Pincus-Nelder e Mead para detecção de dano em estruturas a partir de dados vibracionais." reponame:Repositório Institucional da UFSC, 2014. https://repositorio.ufsc.br/xmlui/handle/123456789/130928.
Full textAbstract:
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Civil, Florianópolis, 2014.Made available in DSpace on 2015-03-18T20:57:38Z (GMT). No. of bitstreams: 1 332871.pdf: 3704219 bytes, checksum: 4e33d2bf52093e56ccd8cc577f3f2076 (MD5) Previous issue date: 2014
Neste estudo, uma proposta de aperfeiçoamento do algoritmo deotimização híbrido estocástico-determinístico Pincus - Nelder e Mead(P-NMA) para detecção de dano em estruturas a partir de dadosvibracionais é apresentada. A formulação da função objetivo para oproblema de minimização é estabelecido pela diferença entre parâmetrosdinâmicos experimentais da estrutura na condição com dano e aquelescalculados utilizando um modelo de elementos finitos (MEF) querepresenta tal condição. Uma estratégia que permite acelerar aconvergência do algoritmo híbrido P-NMA Original para o problema deidentificação de dano é desenvolvida, sendo o algoritmo resultante aquidesignado por P-NMA Modificado. Para se poder ter uma base deescolha de parâmetros envolvidos na parte estocástica do algoritmo,funções testes de otimização global foram utilizadas. Em seguida, cincoexemplos numéricos de identificação de dano, todos retirados daliteratura, nomeadamente, uma viga simplesmente apoiada, uma viga embalanço, duas treliças planas e um pórtico plano com vários cenários dedano são apresentados. Os parâmetros dinâmicos utilizados nestetrabalho (frequências naturais e formas modais) são obtidos através dasolução do problema de autovalores. Para simular as características dainformação obtida por meio de um ensaio dinâmico real, foi consideradaa existência de apenas poucos modos de baixa frequência e também foianalisada a influência do ruído nas medições, que inclui igualmente aimprecisão na coleta de dados. Para testar a precisão e eficiência doalgoritmo resultante do aperfeiçoamento/modificações implementadas(o algoritmo P-NMA Modificado), uma comparação dos resultadosobtidos por meio deste novo algoritmo proposto e do algoritmo P-NMAOriginal é realizada. Além disso, os resultados do último exemplonumérico (pórtico plano) são comparados com aqueles existentes naliteratura, na qual o algoritmo P-NMA Original e o algoritmo genético(AG) foram utilizados. Em todos os casos analisados, as modificaçõesimplementadas funcionaram bem e os resultados foram promissores, oalgoritmo híbrido P-NMA Modificado foi mais preciso e apresentoumenor custo computacional comparativamente ao algoritmo híbrido PNMAOriginal e AG.
Abstract : In this study, an improvement in the hybrid stochastic-deterministicoptimization algorithm Pincus-Nelder and Mead (P-NMA) for vibrationbaseddamage detection in structures is proposed. The formulation of theobjective function for the minimization problem is established by thedifference between experimental dynamic parameters of the damagedstructure and those calculated using a finite element model (FEM) thatrepresents such condition. A strategy which allows a quick convergenceof the Original hybrid algorithm P-NMA for the damage identificationproblem is developed, and the resulting algorithm is denominated hereas Modified P-NMA. In order to have a basis for the choice ofparameters involved in the stochastic part of the hybrid algorithm, testfunctions for global optimization were used. Thereafter, five numericalexamples, all taken from literature, namely, a simply supported beam, acantilever beam, two plane trusses and a portal plane frame with severaldamage scenarios are presented. The dynamic parameters used in thiswork (natural frequencies and mode shapes) are obtained by solving theeigenvalue problem. To simulate the characteristics of informationobtained in a real dynamic test, only a few modes of low frequency wereconsidered and the influence of noise in the measurements, whichinclude the errors during data collection was also analyzed. To test theaccuracy and efficiency of the resultant algorithm from theimprovement/ implemented modifications (the Modified hybrid PNMA),a comparison of the results obtained from this new proposedalgorithm and the Original P-NMA algorithm is performed. In addition,the results of the last numerical example (portal plane frame) arecompared with those available in the literature, where the Original PNMAalgorithm and the genetic algorithm (GA) were used. In allanalyzed cases, the implemented improvements were satisfactory andthe results were promising, the Modified hybrid P-NMA algorithm wasmore accurate and had lower computational cost compared to theOriginal hybrid P-NMA algorithm and GA.
5
Nascimento, Luiz Sérgio Vasconcelos do. "Estudo da operação otimizada aplicada a um sistema de reservatórios destinado à geração de energia elétrica." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/18/18138/tde-25062006-130848/.
Full textAbstract:
Uma das aplicações mais importantes da análise de sistemas no planejamento de recursos hídricos diz respeito à determinação de estratégias operacionais de sistemas de múltiplos reservatórios, elementos indispensáveis aos aproveitamentos hídricos, cuja operação é alvo de análises que podem envolver muitas restrições e variáveis de decisão. Fica evidenciada, portanto, a necessidade de a operação destes ser otimizada, propiciando assim, o seu melhor aproveitamento, com o menor custo para a sociedade. A presente pesquisa estuda a operação otimizada de um sistema de reservatórios destinado a geração de energia elétrica, usando um modelo híbrido composto de algoritmos genéticos e o SIMPLEX de Nelder e Mead acoplado à programação linear sucessiva. Em conformidade com a recente proposta de Reis et al. (2005), o problema de otimização é resolvido através da decomposição em subproblemas seqüenciais independentes relativos a cada estágio de operação, conectados entre si por supor que os volumes dos reservatórios no final de cada estágio correspondam ao estado do sistema no início do estágio subseqüente. Para estimular a utilização mais eficiente dos volumes armazenados, no suprimento das demandas hídricas dos estágios futuros, são aplicados fatores de redução de custo (FRCs) sobre os volumes armazenados remanescentes no final de cada estágioOne of the most important uses for system analysis in water resources planning is the determination of the operational strategy for multiple reservoir systems, fundamental to better water supply, whose operation is the purpose of analysis that may involve many operation constraints and decision variables. Stay clear, so, the need of optimize their operation, creating in this manner, its best utilization with the less cost to society. This research on the optimal operation of a reservoir system has hydropower generation as its main objective. The optimization framework employs a hybrid model which corresponds to a combination of genetic algorithms and SIMPLEX of Nelder e Mead before employing successive linear programming. Accordant to recent Reis et. al (2005) proposal, the problem of optimizing is solved through decomposition in independents sequential sub problems related to each stage of operation, connected among themselves by supposing that reservoir storage at the end of each stage corresponds to the system state at the beginning of the subsequent stage. To promote the most efficient use of storage for water supply in future stages, FRC (cost reduction factors) are applied on the storage left at the end of each stage
6
Póvoa, Caio José Fernandes. "Estratégias de otimização de trajetos e alocação de torres em projetos de linhas de transmissão aéreas." Universidade Federal de Goiás, 2018. http://repositorio.bc.ufg.br/tede/handle/tede/8294.
Full textAbstract:
Submitted by Liliane Ferreira (ljuvencia30@gmail.com) on 2018-04-04T11:42:16Z
No. of bitstreams: 2
Dissertação - Caio José Fernandes Póvoa - 2018.pdf: 6079271 bytes, checksum: 5efa21665d3c5f3bf6b4a58652fff6b4 (MD5)
license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-04-04T13:23:10Z (GMT) No. of bitstreams: 2 Dissertação - Caio José Fernandes Póvoa - 2018.pdf: 6079271 bytes, checksum: 5efa21665d3c5f3bf6b4a58652fff6b4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)
Made available in DSpace on 2018-04-04T13:23:10Z (GMT). No. of bitstreams: 2 Dissertação - Caio José Fernandes Póvoa - 2018.pdf: 6079271 bytes, checksum: 5efa21665d3c5f3bf6b4a58652fff6b4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-03-22
This dissertation of master degree describes methods of optimizing routes and allocating towers of overhead power lines, with the objective of meeting technical, structural and constructive constraints, and reducing financial costs. The generated solutions are graphically presented through the transmission line profile and its 3-dimension representation upon the elevation map of the area. For the projects evaluation, elements of structural analysis are used, highlighting the Matrix Structural Analysis for the study of efforts and deformations in the towers and their components. Three methods are proposed, each one using different approaches. First, it will be shown an optimization algorithm based on Evolutionary Computation, characterized by the application of natural selection on individuals generated from mutations and genetic crossover. The second algorithm was inspired by the well-known Nelder-Mead optimization method. The triangular transformations addressed in the original method were adapted and physically implemented to transmission lines. The last optimization algorithm presented is a hybridization of the two previous methods. Finally, a performance comparison of the algorithms, in which each one of them will be applied to three different cases, will be carried out in order to validate them.
Esta dissertação de mestrado descreve métodos de otimização de trajetos e alocação de torres de linhas aéreas de transmissão de energia elétrica, com o objetivo de obedecer a restrições técnicas, estruturais e construtivas, e de reduzir custos financeiros. As soluções encontradas são apresentadas graficamente a partir da plotagem do perfil da linha de transmissão, e da sua representação em três dimensões sobre o mapa de relevo da região. Para a avaliação dos projetos, utilizam-se elementos de análise estrutural, destacando-se a Análise Estrutural Matricial para o estudo dos esforços e deformações nas torres e seus componentes. São propostos três métodos que utilizam abordagens diferentes. Primeiramente, será considerado um algoritmo de otimização baseado na Computação Evolucionária, caracterizando-se pela aplicação da seleção natural ao longo de gerações, em indivíduos gerados a partir de mutações e recombinações. O segundo algoritmo apresentado é inspirado no consagrado método de Nelder-Mead, sendo as transformações triangulares, por ele apresentadas, adaptadas e implementadas fisicamente a linhas de transmissão. O último método de otimização é uma hibridação dos dois métodos anteriores. Por fim, será feita uma comparação de desempenho dos algoritmos apresentados, a partir da aplicação de cada um deles a três estudos de caso distintos para validá-los.
7
Gasperoni, Samuele. "Studio di un algoritmo di controllo di temperatura per ganasce termosigillanti in macchine per packaging." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9715/.
Full textAbstract:
Gli obiettivi dell'elaborato sono lo studio e la programmazione di un algoritmo di controllo di temperatura per le superfici termosaldanti di macchine per il packaging (confezionatrici in film a file multiple) prodotte dal committente, OMAG srl.
L'algoritmo è implementato tramite il software SoMachineMotion v.4.2, prodotto da Schneider Electrics spa.
Il controllo è di tipo in anello chiuso in retroazione, con temocoppie e resistenze di riscaldamento con modulazione PWM.
Ci si è inizialmente occupati di testare su banco prova varie tipologie di regolatori: a relay, a isteresi, a ricerca diretta del duty cycle, TBH, con approccio misto TBH/integratore di Clegg, PID.
I diversi metodi di regolazione sono stati valutati sulla base di una serie di metri di giudizio (precisione dell'inseguimento, prestazioni statiche e dinamiche, flessibilità, peso computazionale, facilità implementativa), pesati secondo i requisiti imposti dal committente.
Le metodologie selezionate sono state PID e TBH/Clegg integrator; quest'ultima ha dato risultati assai soddisfacenti, pur essendo un metodo monoparametrico.
Si sono quindi studiate diverse modalità per la taratura del regolatore PID, in particolare: tuning in anello chiuso con metodo a relay per la fase di pretuning, algoritmo di Nelder-Mead, per la ricerca diretta continua dei valori che minimizzano l'errore integrale, per un selftuning adattivo.
Si è infine proceduto ad implementare le soluzioni individuate in un software robusto, che rispetti gli standard del settore e si sono inoltre sviluppate una serie di funzionalità aggiuntive, quali: modulazione software PWM, preriscaldamento, handling errori/warning, filtraggio segnali in/out.
Si è addizionalmente sviluppato un modello matematico predittivo dell'evoluzione del sistema, che potrebbe servire, in un futuro sviluppo, come base per un controllo model-based in cascata al controllo in retroazione studiato.
8
Martins, Guilherme de Frias. "Optimização de esforços em estruturas: influência da localização e rigidez dos apoios." Master's thesis, Faculdade de Ciências e Tecnologia, 2012. http://hdl.handle.net/10362/8668.
Full textAbstract:
Dissertação para obtenção do Grau de Mestre
em Engenharia Civil - Perfil EstruturasNo presente trabalho é apresentado um procedimento para optimização estrutural dos esforços em vigas e grelhas, em função da posição e rigidez dos seus apoios. A optimização é efectuada com recurso a métodos de optimização não-linear, nomeadamente os algoritmos de procura directa de Nelder-Mead e os algoritmos genéticos. Ambos os algoritmos estão disponíveis na ferramenta de optimização do MATLAB, optimtool. Para a realização da análise estrutural foram criados dois algoritmos baseados no método dos elementos finitos, sendo um para análise de vigas e o outro para análise de grelhas. A codificação do modelo estrutural foi feita também no programa MATLAB, de modo a facilitar todo o processo de optimização. Foram realizados vários exemplos de optimização estrutural com o objectivo de comprovar a utilidade do processo proposto. Com base nos resultados obtidos, verificou-se que a optimização da posição e rigidez dos apoios permite uma diminuição significativa dos esforços que actuam nas estruturas.
9
Zidani, Hafid. "Représentation de solution en optimisation continue, multi-objectif et applications." Phd thesis, INSA de Rouen, 2013. http://tel.archives-ouvertes.fr/tel-00939980.
Full textAbstract:
Cette thèse a pour objectif principal le développement de nouveaux algorithmes globaux pour la résolution de problèmes d'optimisation mono et multi-objectif, en se basant sur des formules de représentation ayant la tâche principale de générer des points initiaux appartenant à une zone proche du minimum globale. Dans ce contexte, une nouvelle approche appelée RFNM est proposée et testée sur plusieurs fonctions non linéaires, non différentiables et multimodales. D'autre part, une extension à la dimension infinie a été établie en proposant une démarche pour la recherche du minimum global. Par ailleurs, plusieurs problèmes de conception mécanique, à caractère aléatoire, ont été considérés et résolus en utilisant cette approche, avec amélioration de la méthode multi-objectif NNC. Enfin, une contribution à l'optimisation multi-objectif par une nouvelle approche a été proposée. Elle permet de générer un nombre suffisant de points pour représenter la solution optimale de Pareto.
10
Gomes, Fabrício Maciel [UNESP]. "Diferentes métodos de aglutinação para melhoria de processos com múltiplas respostas." Universidade Estadual Paulista (UNESP), 2015. http://hdl.handle.net/11449/132419.
Full textAbstract:
Submitted by FABRÍCIO MACIEL GOMES null (fabricio@dequi.eel.usp.br) on 2016-01-04T00:06:19Z
No. of bitstreams: 1
Tese_Fabricio_Maciel_Gomes.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5)Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-01-06T16:12:19Z (GMT) No. of bitstreams: 1 gomes_fm_dr_guara.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5)
Made available in DSpace on 2016-01-06T16:12:19Z (GMT). No. of bitstreams: 1 gomes_fm_dr_guara.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5) Previous issue date: 2015-12-15
Empresas não medem esforços para aperfeiçoar seus processos e produtos de acordo com diferentes critérios para satisfazer as exigências e necessidades dos clientes em busca de um padrão de competitividade superior ao de suas concorrentes. Neste cenário é muito comum a necessidade de se estabelecer condições que resultem na melhoria de mais de um critério de forma simultânea. Neste trabalho foi realizada uma avaliação da utilização de quatro métodos que utilizam as Meta-heurísticas Recozimento Simulado, Algoritmo Genético, Recozimento Simulado combinado com o método Nelder Mead Simplex e algoritmo genético combinado com o método Nelde-Mead simplex para o estabelecimento de melhoria das condições de processos com múltiplas respostas. Para a avaliação dos métodos propostos foram utilizados problemas-teste criteriosamente selecionados na literatura de forma a serem analisados casos com diferente número de variáveis, número de respostas e tipos de resposta. A aglutinação das respostas foi realizada por quatro métodos diferentes: Desirability, Desvio Médio Percentual, Programação por Compromisso e Programação por Compromisso normalizada pela distância euclidiana. A avaliação dos métodos foi realizada por meio de comparação entre os resultados obtidos na utilização de um mesmo método de aglutinação, determinando assim a eficiência do método de busca. Os resultados obtidos na avaliação dos métodos sugerem a aplicação do método do algoritmo genético quando se pretende estabelecer parâmetros que resultem na melhoria de processos com múltiplas respostas, em particular quando essas respostas são modeladas por equações com termos cúbicos, independentemente do número de termos que possam conter, do tipo de respostas e do número de variáveis.
Companies go to great lengths to improve its processes and products according to different criteria to meet the demands and needs of customers looking for a higher standard of competitiveness to that of their competitors. This scenario is very common the need to establish conditions that result in the improvement of more than one criterion simultaneously. This work was carried out an evaluation of the use of four methods that use Metaheuristics Simulated Annealing, Genetic Algorithms, Simulated Annealing combined with the Nelder Mead Simplex method and genetic algorithm combined with Nelde Mead simplex method for the improvement of establishing the conditions of processes with multiple answers. For the evaluation of the proposed test methods were used in the literature problems carefully selected in order to be analyzed cases with different numbers of variables, response numbers and types of responses. In this research we used the average percentage deviation function as a way to bring together the answers. The agglutination of the answers was performed by four different methods: Desirability, Average Percentage Deviation, Compromise Programming and Compromise Programming normalized by Euclidean distance. The evaluation method was performed by comparison between the results obtained in using the same bonding method, thereby determining the efficiency of the search method. The results obtained in the evaluation of the methods suggest the application of the genetic algorithm method when you want to set parameters that result in the improvement of processes with multiple answers, particularly when these responses are modeled by equations with cubic terms, regardless of the number of terms that can contain the type of responses and the number of variables.
Book chapters on the topic "Nelder-Mead algoritmus"
1
Reddy, Annem Abhishek, Maheedhar Vundela, and G. Manju. "Portfolio Optimization Using Genetic Algorithms with Nelder–Mead Algorithm." In Proceedings of 6th International Conference on Recent Trends in Computing, 197–206. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4501-0_19.
Full text
2
Marandi, Parisa Jalili, Muharram Mansooriazdeh, and Nasrollah Moghadam Charkari. "The Effect of Re-sampling on Incremental Nelder-Mead Simplex Algorithm: Distributed Regression in Wireless Sensor Networks." In Wireless Algorithms, Systems, and Applications, 420–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88582-5_40.
Full text
3
Ali, Shawkat, and Kate A. Smith. "Kernel Width Selection for SVM Classification." In Data Warehousing and Mining, 3308–23. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-951-9.ch209.
Full textAbstract:
The most critical component of kernel based learning algorithms is the choice of an appropriate kernel and its optimal parameters. In this paper we propose a rule based meta-learning approach for automatic radial basis function (rbf) kernel and its parameter selection for Support Vector Machine (SVM) classification. First, the best parameter selection is considered on the basis of prior information of the data with the help of Maximum Likelihood (ML) method and Nelder-Mead (N-M) simplex method. Then the new rule based meta-learning approach is constructed and tested on different sizes of 112 datasets with binary class as well as multi class classification problems. We observe that our rule based methodology provides significant improvement of computational time as well as accuracy in some specific cases.
Conference papers on the topic "Nelder-Mead algoritmus"
1
Trabia, Mohamed B. "A Hybrid Fuzzy Simplex Genetic Algorithm." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dac-14231.
Full textAbstract:
Abstract Nelder and Mead Simplex (NMS) algorithm is an effective nonlinear programming technique. Trabia and Lu (1999) recently presented a novel algorithm, Fuzzy Simplex (FS), which improved the efficiency of Nelder and Mead Simplex by using fuzzy logic to determine the orientation and size of the simplex. While Fuzzy Simplex algorithm can be successfully used to search a wide variety of functions, it suffers, as other simplex algorithms, from its dependence on the initial guess and the original simplex size. This paper addresses this problem by combining the Fuzzy Simplex with Genetic Algorithm (GA) in a hybrid algorithm. Standard test problems are used to evaluate the efficiency of the algorithm. The algorithm is also applied successfully to several engineering design problems. The Hybrid GA Fuzzy Simplex algorithm generally results in a faster convergence.
2
Nassef, Ashraf O., Hesham A. Hegazi, and Sayed M. Metwalli. "A Hybrid Genetic-Direct Search Algorithm for the Shape Optimization of Solid C-Frame Cross-Sections." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dac-14295.
Full textAbstract:
Abstract The hybridization of different optimization methods have been used to find the optimum solution of design problems. While random search techniques, such as genetic algorithms and simulated annealing, have a high probability of achieving global optimality, they usually arrive at a near optimal solution due to their random nature. On the other hand direct search methods are efficient optimization techniques but linger in local minima if the objective function is multi-modal. This paper presents the optimization of C-frame cross-section using a hybrid optimization algorithm. Real coded genetic algorithms are used as a random search method, while Nelder-Mead is used as a direct search method, where the result of the genetic algorithm search is used as the starting point of direct search. Traditionally, the cross-section of C-frame belonged to a set of primitive shapes, which included I, T, trapezoidal, circular and rectangular sections. The cross-sectional shape is represented by a non-uniform rational B-Splines (NURBS) in order to give it a kind of shape flexibility. The results showed that the use of Nelder-Mead with Real coded Genetic Algorithms has been very significant in improving the optimum shape of a solid C-frame cross-section subjected to a combined tension and bending stresses. The hybrid optimization method could be extended to more complex shape optimization problems.
3
Hegazi, Hesham A., Ashraf O. Nassef, and Sayed M. Metwalli. "Shape Optimization of NURBS Modeled 3D C-Frames Using Hybrid Genetic Algorithm." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/dac-34107.
Full textAbstract:
The present paper introduces a new methodology for designing machine element shapes. The element is represented using non-uniform rational B-Spline (NURBS) in order to give it a form of shape flexibility. A special form of genetic algorithms known as real-coded genetic algorithms is used to conduct the search for the design objectives. Shape optimization of 3D C-frames are used as an application of the proposed methodology. The design parameters of these frames include the dimensions of their cross-sections, which should be chosen to withstand the applied loads and minimize the element’s overall weight. In a further development, the hybridization of different optimization methods has been used to find the optimum shape of the element. Real coded genetic algorithm is used as a random search method, while Nelder-Mead is used as a direct search method, where the result of the genetic algorithm search is used as the starting point of direct search. The results showed that the use of Nelder-Mead with Real coded Genetic Algorithms has been very significant in improving the optimum shape of a solid 3D C-frames subjected to a combined tension and bending stresses. The hybrid optimization method could be extended to more complex shape optimization problems. For the purpose of analysis, curved beam theory is applied on local cross-sections on the NURBS surface. A finite elements analysis was conducted on SDRC-IDEAS for verifying the results obtained using the curved beam theory.
4
Zheng, Kaifeng, Chao Wang, Weizheng An, and Likun Ge. "A Hybrid Method Combining Tab Search and Nelder-Mead Algorithms for Global Continuous Optimization Problems." In 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2018. http://dx.doi.org/10.1109/cscwd.2018.8465387.
Full text
5
Morales-Romero, J. J., M. A. Reyes-Barranca, L. M. Flores-Nava, and E. R. Espinosa-Garcia. "Proposal for training a Cellular Neural Network using a Hybrid Artificial Bee Colony and Nelder-Mead Algorithms." In 2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE). IEEE, 2020. http://dx.doi.org/10.1109/cce50788.2020.9299146.
Full text
6
Aydın, Kemal Bartu, Levent Aydin, and Fethullah Güneş. "Stochastic Optimization of TiO2-Graphene Nanocomposite by Using Neuro-Regression Approach for Maximum Photocatalytic Degradation Rate." In International Students Science Congress. Izmir International Guest Student Association, 2021. http://dx.doi.org/10.52460/issc.2021.044.
Full textAbstract:
TiO2 is one of the most common materials for photocatalytic applications due to its stability, affordability, and photoactive efficiency. However, it has some drawbacks, such as limited solar radiation response and quick recombination of excitons. Using graphene could be one of the methods to enhance the photocatalytic properties of TiO2. This study intends to optimize the photocatalytic performance of TiO2/Graphene (TiO2/G) nanocomposite by using neuro-regression analysis. In the analysis, the effect of some hydrothermal synthesis parameters, namely, amount of graphene oxide, ethanol/water ratio, and hydrothermal reaction time on the photocatalytic activity of TiO2/G nanocomposite, have been investigated. The parameters were determined from a literature study focused on overcoming the drawbacks of TiO2 by combining it with graphene oxide. Nelder-Mead, Simulated Annealing, Differential Evolution, and Random Search algorithms are used to obtain the optimum synthesis parameters for maximum photocatalytic activity in the optimization process. The results are indicated that all algorithms give the realizable value for design variables and photodegradation rate.
7
Mekhilef, Mounib, and Mohamed B. Trabia. "Successive Twinkling Simplex Search Optimization Algorithms." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/dac-21132.
Full textAbstract:
Abstract Simplex algorithms have been proven to be a reliable nonlinear programming pattern search algorithm. The effectiveness of simplex however reduces when the solved problem has large number of variables, several local minima, or when initial guess is not readily available. Recent results obtained by introducing a technique of random selection of the variables in optimization processes, encouraged studying the effect of this idea on the Nelder & Mead version of the simplex algorithm to improve its semi-global behavior. This paper proposes several enhancements to the simplex. The algorithm is run for several attempts. Each attempt uses the final answer of the previous attempt as an initial guess. At each attempt, the search starts by generating a simplex with n+1 vertices. A random subset of the variables is involved in the movement (reflection, expansion, contraction, shrinking) of the simplex. This process is called twinkling. The paper presents several variations of twinkling the simplex. The random nature of the algorithm lends itself to problems with large dimensionality or complex topography. The algorithm is applied successfully to several engineering design problems. The results compare favorably with both regular simplex and genetic algorithms.
8
Yalcin, Refet A., and Hakan Ertu¨rk. "Optimization of Pigmented Coatings for Concentrating Solar Thermal Applications." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-63322.
Full textAbstract:
Spectrally selective coatings are used in absorbers of solar collectors to maximize efficiency of solar thermal energy systems. Desired coating should have high absorptance at solar wavelengths and low emittance at the wavelengths where absorber emits heat. This study focuses on pigmented coatings that consist of a binder and uniformly distributed nano-particles known as pigments that exhibit the desired spectrally selective behavior. Radiative behavior of coatings depend on coating thickness, pigment size, concentration, and the optical properties of binder and pigment materials. In order to understand the effect of these parameters, a radiative model of the pigmented coatings is developed using Lorentz-Mie theory in conjunction with Hartel theory to incorporate the multiple scattering effects. Through the solution of the radiative transfer equation by the four flux method, spectral emittance is predicted. Design of such a coating is formulated as an inverse problem of estimating design variables yielding the desired spectral emittance of the ideal coating. The nonlinear problem is solved by optimization applying two algorithms for the solution. While both algorithms are capable of providing the same solution, the convergence of Quasi Newton method is found to be superior to that of Nelder Mead simplex algorithm.
9
Savran, Melih, Asil Ayaz, and Tuğrul Uslu. "Modeling and Optimization of 3D Printed PLA Material for Maximum Flexural Strength Using Multiple Nonlinear Neuro Regression Analysis." In International Students Science Congress. Izmir International Guest Student Association, 2021. http://dx.doi.org/10.52460/issc.2021.033.
Full textAbstract:
Fused deposition modelling (FDM) is a growing additive manufacturing method to produce complex objects without geometrical limitations. In addition, mechanical strength, dimensional accuracy, product development cycle time, and surface properties can be improved depending on the application of the best settings of design variables. There are various printing parameters which influence the mechanical properties and quality of FDM parts. In this study, appropriate printing parameters were determined to obtain desired quality on mechanical properties and dimensional accuracy. Then full factorial design was employed to form experiment set including process parameters. Multiple nonlinear neuro-regression analysis was used for modeling of FDM process. The present study aims at optimization of the FDM process parameters including infill pattern, infill density and build orientation on flexural strength and strain for polylactide (PLA) material. In this regard, optimization algorithms Differential Evolution and Nelder Mead were used to find the best design or elite designs. Third-order polynomial model and hybrid model including polynomial and logarithmic terms were employed as an objective function to define physical phenomena regarding flexural strength and strain, respectively. It was found that (i) maximum flexural strength as 99.66 MPa using a cubic pattern, flat orientation, and 90 % infill density, (ii) minimum ultimate strain as 1.102 % for gyroid pattern, flat orientation, and 47 % infill density.
10
Sanaye, Sepehr, Behrooz Farshi, and Hashem Turk. "Optimum Turbine Extraction Pressures for Maximum Efficiency in Steam Power Plant Cycle." In International Joint Power Generation Conference collocated with TurboExpo 2003. ASMEDC, 2003. http://dx.doi.org/10.1115/ijpgc2003-40205.
Full textAbstract:
In design of a real steam power plant cycle with seven or eight open and closed feed water heaters, choosing the appropriate turbine extraction pressures has important effect on the cycle efficiency. By considering the steam cycle thermal efficiency as an objective function, various optimization techniques including the Full Search, Hook-Jeeves and Nelder-Mead schemes were applied for selecting the proper arrangement of feed water heaters and the optimum steam turbine extraction pressures. In order to optimally design and accurately analyze the behavior of steam power plant cycles, a modular software based on object oriented programming has been developed. Steam cycle elements used in this software while forming a set of independent objects, collectively present an inter-related behavior. In the design environment of the software, a complete steam cycle power plant can be visually designed and analyzed. The correct performance of this software in calculation of the state variations at various cycle points and the cycle thermal efficiency was checked and verified. The values of extraction pressures and mass flow rates at the optimum design point were assessed and found to be in agreement with the corresponding values of existing power plants. Based on the literature available, incorporation of all the design features involving modular aspect with optimization search using several algorithms and comparisons made of the results with actual power plant performances have not yet been successfully accomplished in a software package.