Relevant bibliographies by topics / Algorithme du simplexe

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Academic literature on the topic 'Algorithme du simplexe'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Algorithme du simplexe"

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Zhang, Jing Jun, Huan Chen, and Rui Zhen Gao. "An Improved Genetic Algorithm Based on K2(m) Triangulation of Continuous Self-Mapping." Advanced Materials Research 295-297 (July 2011): 2515–20. http://dx.doi.org/10.4028/www.scientific.net/amr.295-297.2515.

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In this paper an improved genetic algorithm based on the simplex self-mapping fixed point algorithm is proposed. With this algorithm, the optimal problem of n-dimensional closure function will be transformed as the solution of approximate fixed point problem of n-dimensional standard simplexes by homeomorphism mapping. The genetic operators relying on the integer labels are designed. In this case, whether every individual loading simplex of the population is a completely labeled simplex can be used as an objective convergence criterion. The simulation results demonstrate that the proposed algorithm is valid and effective.
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Trabia, Mohamed B., and Xiao Bin Lu. "A Fuzzy Adaptive Simplex Search Optimization Algorithm." Journal of Mechanical Design 123, no. 2 (1999): 216–25. http://dx.doi.org/10.1115/1.1347991.

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Most optimization algorithms use empirically-chosen fixed parameters as a part of their search strategy. This paper proposes to replace these fixed parameters by adaptive ones to make the search more responsive to changes in the problem by incorporating fuzzy logic in optimization algorithms. The proposed ideas are used to develop a new adaptive form of the simplex search algorithm whose objective is to minimize a function of n variables. The new algorithm is labeled Fuzzy Simplex. The search starts by generating a simplex with n+1 vertices. The algorithm then repeatedly replaces the point with the highest function value by a new point. This process has three components: reflecting the point with the highest function value, expanding, and contracting the simplex. These operations use fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. Standard minimization test problems are used to evaluate the efficiency of the algorithm. The Fuzzy Simplex algorithm generally results in a faster convergence. Robustness and sensitivity of the algorithm are also considered. The Fuzzy Simplex algorithm is also applied successfully to several engineering design problems. The results of the Fuzzy Simplex algorithm compare favorably with other available minimization algorithms.
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De-Graft Acquah, Henry, and Sarah Acquah. "Interior point algorithm for solving farm resource allocation problem." Applied Studies in Agribusiness and Commerce 11, no. 1-2 (2017): 45–49. http://dx.doi.org/10.19041/apstract/2017/1-2/6.

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This paper introduces interior point algorithm as an alternative approach to simplex algorithm for solving farm resource allocation problem. The empirical result of interior point algorithm is compared with that of the simplex algorithm. It goes further to address a profit maximization problem. The result revealed several relevant patterns. Results of the interior point algorithm is similar to that of the simplex algorithm. Findings indicated that in both algorithms, the farm is to produce peppers, wheat which is irrigated and weeded manually, hire additional month of labour, and also purchase urea and muriate fertilizer to realize a similar amount of profit. Additionally, both algorithms suggested that practicing crop rotation where beans, if grown, should be altered with wheat cannot be possible since no beans will be grown. The Simplex algorithm saves 39 iterations over Interior Point algorithm in solving the farm resource allocation problem. The findings demonstrate that the interior point algorithm offers a useful alternative to the simplex algorithm when addressing farm resource allocation problem.
 JEL code: D24, D57, C61, C63, C67
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Zandavi, Seid Miad, Vera Chung, and Ali Anaissi. "Multi-user Remote Lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm." ACM/IMS Transactions on Data Science 2, no. 2 (2021): 1–13. http://dx.doi.org/10.1145/3437260.

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The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. The hybrid optimization algorithm, hybridization of the Nelder-Mead Simplex algorithm, and Non-dominated Sorting Genetic Algorithm (NSGA), named Simplex Non-dominated Sorting Genetic Algorithm (SNSGA), is proposed to optimize the timetable problem for the remote laboratories to coordinate shared access. The proposed algorithm utilizes the Simplex algorithm in terms of exploration and NSGA for sorting local optimum points with consideration of potential areas. SNSGA is applied to difficult nonlinear continuous multimodal functions, and its performance is compared with hybrid Simplex Particle Swarm Optimization, Simplex Genetic Algorithm, and other heuristic algorithms. The results show that SNSGA has a competitive performance to address timetable problems.
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Amrullah, Muhammad. "PEMODELAN PEMROGRAMAN LINIER DENGAN KOEFISIEN FUNGSI OBJEKTIF, FUNGSI KENDALA DAN VARIABEL KEPUTUSAN BERBENTUK BILANGAN KABUR BESERTA APLIKASINYA." Jurnal Matematika, Statistika dan Komputasi 16, no. 1 (2019): 85. http://dx.doi.org/10.20956/jmsk.v16i1.5802.

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Abstrak Dalam penelitian ini penulis akan mengusulkan algoritma untuk memodelkan masalah pemrograman linear kabur dengan bilangan kabur trapesium menggunakan metode simpleks. Secara khusus dalam aplikasi teori ini adalah masalah pengambilan keputusan pemrograman linear kabur dengan menyajikan metode baru untuk menyelesaikan masalah pemrograman linier kabur dengan menggunakan fungsi ranking. Pada dasarnya, langkah-langkah dalam metode penelitian ini sama dengan dengan metode simpleks yang digunakan untuk memecahkan masalah pemrograman linier tegas.Kata kunci: Fuzzy linear programming, fungsi ranking, metode simpleks. AbstractIn this paper author shall propose an algorithm for solving fuzzy linear programming problems with trapezoidal numbers using a simplex method. In particular, an application of this theory in decision making problems is fuzzy linear programming with a new method for solving fuzzy linear programming problems, by use of rank function. Basically, our method is similar to simplex method that was used for solving linear programming problems in crisp environment before.Keywords: Fuzzy linier programming, rank function, simplex method.
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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.

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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.
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Trabia, Mohamed B. "A Hybrid Fuzzy Simplex Genetic Algorithm." Journal of Mechanical Design 126, no. 6 (2004): 969–74. http://dx.doi.org/10.1115/1.1803852.

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This paper presents a novel hybrid genetic algorithm that has the ability of the genetic algorithms to avoid being trapped at local minimum while accelerating the speed of local search by using the fuzzy simplex algorithm. The new algorithm is labeled the hybrid fuzzy simplex genetic algorithm (HFSGA). Standard test problems are used to evaluate the efficiency of the algorithm. The algorithm is also applied successfully to several engineering design problems. The HFSGA generally results in a faster convergence toward extremum.
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Ploskas, Nikolaos, Nikolaos Samaras, and Jason Papathanasiou. "A Decision Support System for Solving Linear Programming Problems." International Journal of Decision Support System Technology 6, no. 2 (2014): 46–62. http://dx.doi.org/10.4018/ijdsst.2014040103.

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Linear programming algorithms have been widely used in Decision Support Systems. These systems have incorporated linear programming algorithms for the solution of the given problems. Yet, the special structure of each linear problem may take advantage of different linear programming algorithms or different techniques used in these algorithms. This paper proposes a web-based DSS that assists decision makers in the solution of linear programming problems with a variety of linear programming algorithms and techniques. Two linear programming algorithms have been included in the DSS: (i) revised simplex algorithm and (ii) exterior primal simplex algorithm. Furthermore, ten scaling techniques, five basis update methods and eight pivoting rules have been incorporated in the DSS. All linear programming algorithms and methods have been implemented using MATLAB and converted to Java classes using MATLAB Builder JA, while the web interface of the DSS has been designed using Java Server Pages.
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Irwin, Klee. "Toward the Unification of Physics and Number Theory." Reports in Advances of Physical Sciences 03, no. 01 (2019): 1950003. http://dx.doi.org/10.1142/s2424942419500038.

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This paper introduces the notion of simplex-integers and shows how, in contrast to digital numbers, they are the most powerful numerical symbols that implicitly express the information of an integer and its set theoretic substructure. A geometric analogue to the primality test is introduced: when [Formula: see text] is prime, it divides [Formula: see text] for all [Formula: see text]. The geometric form provokes a novel hypothesis about the distribution of prime-simplexes that, if solved, may lead to a proof of the Riemann hypothesis. Specifically, if a geometric algorithm predicting the number of prime simplexes within any bound [Formula: see text]-simplex or associated [Formula: see text] lattice is discovered, a deep understanding of the error factor of the prime number theorem would be realized — the error factor corresponding to the distribution of the non-trivial zeta zeros, which might be the mysterious link between physics and the Riemann hypothesis [D. Schumayer and D. A. W. Hutchinson, Colloquium: Physics of the Riemann hypothesis, Rev. Mod. Phys. 83 (2011) 307]. It suggests how quantum gravity and particle physicists might benefit from a simplex-integer-based quasicrystal code formalism. An argument is put forth that the unifying idea between number theory and physics is code theory, where reality is information theoretic and 3-simplex integers form physically realistic aperiodic dynamic patterns from which space, time and particles emerge from the evolution of the code syntax.
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MOHAN, S. R., S. K. NEOGY, and T. PARTHASARATHY. "PIVOTING ALGORITHMS FOR SOME CLASSES OF STOCHASTIC GAMES: A SURVEY." International Game Theory Review 03, no. 02n03 (2001): 253–81. http://dx.doi.org/10.1142/s0219198901000385.

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In this paper, we survey the recent literature on computing the value vector and the associated optimal strategies of the players for special cases of zero-sum stochastic games, or in computing a Nash equilibrium point and the corresponding stationary strategies of the players for special cases of nonzero-sum stochastic games, using finite-step algorithms based on pivoting. Examples of finite-step pivoting algorithms are the various simplex-type algorithms, such as the primal simplex or dual simplex method for solving the linear programming problem or Lemke's or Lemke-Howson's algorithm for solving the linear complementarity problem. Also included are Lemke-type algorithms for solving various generalisations of the linear complementarity problem. The survey also includes a few new results and observations.
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Dissertations / Theses on the topic "Algorithme du simplexe"

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Keraghel, Abdelkrim. "Étude adaptative et comparative des principales variantes dans l'algorithme de Karmarkar." Phd thesis, Grenoble 1, 1989. http://tel.archives-ouvertes.fr/tel-00332749.

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Après une description de la méthode de Karmarkar, il est montré que la valeur du pas de déplacement peut être largement améliorée. Les principales difficultés pratiques de la méthode sont discutées. Plus particulièrement, l'hypothèse de connaitre, au départ, la valeur optimale de l'objectif. Diverses extensions et variantes sont étudiées dans le but de relaxer l'hypothèse ci-dessus
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Bouarfa, Abdelkader. "Méthodes de commande par allocation de convertisseurs statiques polyphasés, multi-niveaux : de la modélisation à la mise en oeuvre temps-réel." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30261/document.

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Dans nos travaux, nous nous intéressons à la commande des convertisseurs statiques à grand nombre d'interrupteurs. Le développement des topologies multi-niveaux multi-bras a ouvert l'accès aux domaines de la forte puissance et de la haute qualité harmonique. Outre cette montée en puissance, la commande spéciale de ces dispositifs permet de conférer au convertisseur des fonctionnalités avancées de plus en plus nécessaires, comme la possibilité de filtrage actif des harmoniques, la tolérance aux pannes, la gestion du réactif, les liaisons HVDC, etc. Toutefois, un plus grand nombre d'interrupteurs au sein d'une même structure de conversion se traduit par une forte croissance du nombre de variables de commande, des degrés de liberté et par une explosion combinatoire du nombre de configurations possibles. La synthèse de lois de commande suivant les approches traditionnellement conçues pour les topologies classiques, comme les méthodes de modulation vectorielle fondées sur la représentation géométrique du convertisseur, en devient rapidement fastidieuse pour les nouvelles topologies plus complexes. De plus, les interrupteurs présents en surnombre apportent des redondances fortes qui ne sont pas nécessairement exploitées, ou du moins arbitrairement. Nous proposons une nouvelle approche de commande qui se veut moins dépendante du nombre d'interrupteurs, et qui s'affranchit des limitations induites par les méthodes de modulation géométrique. Notre approche consiste dans un premier temps à formuler de manière algébrique des problèmes de commande qui sont généralement sous-déterminés, témoignant de la présence de redondances ou degrés de liberté, et contraints, car tenant compte des limitations propres aux rapports cycliques. De manière intéressante, ces problèmes offrent une similarité avec les problèmes dits d'allocation de commande rencontrés en aéronautique, en marine ou en robotique. Dans un second temps, dans le but de fournir à chaque période de découpage une solution de commande unique et optimisée, nous concevons de nouvelles méthodes d'allocation pour les convertisseurs statiques fondées sur l'optimisation numérique en ligne à partir de techniques d'optimisation linéaire. En conséquence, les rapports cycliques sont automatiquement optimisés pour satisfaire aux références de tension tout en respectant les saturations et en exploitant les redondances disponibles selon l'état actuel du convertisseur. Nous mettons en lumière les propriétés naturellement offertes par nos méthodes. Notamment, toutes nos solutions de modulation étendent de manière maximale la zone de linéarité du convertisseur. Nous proposons des méthodes d'allocation pour la commande en tension ou en courant de topologies variées : l'onduleur quatre bras deux niveaux, l'onduleur multicellulaire à condensateurs flottants, l'onduleur modulaire multi-niveaux. Concernant les convertisseurs multicellulaires, nos méthodes d'allocation utilisent automatiquement les degrés de liberté disponible pour fournir un équilibrage actif très rapide des tensions de condensateurs flottants. Aussi, grâce à la formulation algébrique des contraintes de commande, nos algorithmes peuvent prendre en compte un défaut sur un interrupteur pour conférer au convertisseur une propriété de tolérance aux fautes du point de vue de la commande<br>In our works, we are interested in control of high-switch-count power converters. The development of multileg, multilevel converters has opened the access to high power and high harmonic quality. The special control of these devices brings to the converter advanced abilities that are more and more requested nowadays, like active harmonic filtering, fault tolerance, active and reactive power transfer, High Voltage Direct Current (HVDC) links, etc. However, a higher number of switches in a conversion structure leads to a higher number of control variables, as well as more redundancies and a combinatorial explosion of the number of possible configurations. The development of control laws resulting from approaches traditionally designed for classical topologies, as for space vector modulation methods, becomes harder for new, much complex topologies. Moreover, the too many available switches bring strong control redundancies that are not necessarily exploited, at least arbitrarily. We propose a new control approach that is expected to be less dependent on the number of switches, and that does not suffer from limitations proper to geometrical modulation methods. Firstly, our approach consists in the algebraic formulation of control problems that are generally under-determined, highlighting the presence of redundancies and degrees of freedom, and constrained, because control limitations are taken into account. Interestingly, a connection can be highlighted to the so-called control allocation problem in flight control, robotics, or marine applications. Secondly, in order to compute a unique and optimized control solution at each switching period, we develop new control allocation methods for power converters based on on-line numerical optimization using linear programming techniques. Consequently, duty cycles are automatically optimized to satisfy voltage references while respecting saturations and exploiting available redundancies depending on the state of the converter. We highlight the properties naturally offered by our methods. In particular, all modulation solutions yield a maximized extension of the linearity range of the converter. We propose control allocation methods for the voltage or current control of many topologies: the four-leg two-level inverter, the multicellular flying capacitor inverter, the modular multilevel inverter
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Szeto, Raymond W. L. (Raymond Wen Li) 1977. "Clamping-simplex methods : improved direct search simplex algorithms." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86829.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.<br>Includes bibliographical references (leaf 66).<br>by Raymond W.L. Szeto.<br>M.Eng.
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CORDEIRO, JOAQUIM PEDRO DE V. "NETWORK SIMPLEX, ALGORITHM E IMPLEMENTATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13219@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Este trabalho busca desenvolver o método Simplex para Redes na solução de problemas de Fluxo de Custo Mínimo. Este método consiste em uma adaptação do método Simplex primal em que são exploradas as características específicas da rede subjacente ao problema ao se buscar a solução ótima em um número finito de árvores geradoras. A árvore geradora ótima será obtida iterativamente através de sucessivas melhorias na estrutura de cada árvore formada. A maior eficiência do Simplex para Redes se dá tanto no menor número de iterações necessárias para se atingir o ótimo, quanto na maior velocidade destas iterações, trata-se, portanto, de um método bastante poderoso na resolução de problemas de Fluxo de Custo Mínimo. Serão, também, abordados aspectos práticos da implementação do algoritmo além da aplicação deste algoritmo implementado em VBA (Visual Basic for Applications) em um problema prático a título de exemplificação.<br>The current work intends to develop a Network Simplex Method for solving Minimum Cost Flow problems. Such method consists of a primal Simplex Method adaptation in which specific characteristics of the network underlying the problem are investigated by searching for the optimal solution within a finite number of spanning trees. The optimal spanning tree is iteratively obtained through successive structure improvements in each formed tree. The higher efficiency of Network Simplex lies both in fewer iterations necessary to achieve the optimum and in the higher speed of these iterations. Therefore, it is a powerful method for solving Minimum Cost Flow Problems. Practical aspects of implementing the algorithm will be discussed, as well as the algorithm´s implementation in VBA (Visual Basic for Applications) through a practical instance.
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Aggarwal, Charu C., Haim Kaplan, and Robert E. 1948 Tarjan. "A Faster Primal Network Simplex Algorithm." Massachusetts Institute of Technology, Operations Research Center, 1996. http://hdl.handle.net/1721.1/5266.

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We present a faster implementation of the polynomial time primal simplex algorithm due to Orlin [23]. His algorithm requires O(nm min{log(nC), m log n}) pivots and O(n2 m ??n{log nC, m log n}) time. The bottleneck operations in his algorithm are performing the relabeling operations on nodes, selecting entering arcs for pivots, and performing the pivots. We show how to speed up these operations so as to yield an algorithm whose running time is O(nm. log n) per scaling phase. We show how to extend the dynamic-tree data-structure in order to implement these algorithms. The extension may possibly have other applications as well.
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Luangpaiboon, Pongchanun. "A comparison of algorithms for automatic process optimisation." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324922.

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Yan, Ping. "Theory of simple genetic algorithms." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446649.

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Valkanova, Elena. "Algorithms for simple stochastic games." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003070.

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Costa, Rogério Rodrigues Lacerda. "Algoritmo genético aplicado à formulação de ração para frangos de corte." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/74/74131/tde-23112017-134715/.

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Este projeto teve por objetivo a implementação de software para formulação de ração de frangos de corte utilizando Algoritmo Genético (AG). A geração da população inicial foi direcionada, impedindo a geração de indivíduos que possuíam características restritivas. Realizou-se três experimentos, sendo o primeiro para definição do tamanho da população, número de gerações e método de seleção de pais, o segundo para comparar a formulação de ração do AG com a do Simplex e o terceiro para verificar a variabilidade de resultados do AG. O experimento 1 foi realizado em delineamento inteiramente ao acaso, com tratamentos arranjados em esquema fatorial 2 x 5 x 19, sendo os fatores: métodos de seleção de pais (roleta e torneio de três), tamanho de população (200, 360, 500, 1.000 e 1.500 indivíduos) e número de geração (10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900 e 1.000), totalizando 190 tratamentos, com 20 repetições resultando em 3.800 observações. A cada observação registrou-se o fitness que foi submetido a análise de variância e quando significativa (P&lt;0,05) aplicou-se o teste de Scott-Knott (5%). No experimento 2 foram formuladas três rações, sendo uma ração pelo método Simplex e duas pelo AG. As rações formuladas com AG utilizaram os parâmetros de tamanho de população, método de seleção de pais e número de gerações definidos no experimento 1. Os resultados obtidos pelo AG proporcionaram rações que apresentam uma diferença média no atendimento das necessidades nutricionais de 0,34% para a ração formulada pelo método roleta e de 0,16% pelo método torneio de três, sendo essas diferenças pequenas e que provavelmente não impactam sobre o desempenho animal e sobre as características de carcaça. A variação de resultados existente no AG, devido a sua característica heurística, foi testada no experimento 3 por intermédio de 100 execuções para cada método de seleção de pais, roleta e torneio de três, utilizando os mesmos parâmetros de tamanho de população e número de gerações das rações formuladas no experimento 2. Os resultados obtidos demonstram baixa dispersão nos dados. Conclui-se que o AG é uma estratégia de otimização eficiente para formulação de rações para frangos de corte, pois aproxima-se do atendimento exato da exigência nutricional, com variação pequena, e com mínimo custo.<br>The objective of the present project was to implement software for the formulation of broiler chicken feed using a Genetic Algorithm (GA). The generation of the initial population was directed, preventing the production of individuals with restrictive characteristics. A total of three experiments were carried out: the first one to define the population size, number of generations, and the method of parent selection; the second to compare ration formulation using the GA with that of the Simplex method, and the third to verify result variability using the GA. Experiment 1 was performed in a completely randomized design, with arranged treatments in a 2 x 5 x 19 factorial scheme, assessing the following factors: parent selection methods (roulette-wheel selection and tournament selection of three), population size (200, 360, 500, 1 000 and 1 500 individuals), and number of generations (10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900 and 1 000 ), totaling 190 treatments, with 20 repetitions each, resulting in 3 800 recordings. At each observation, the registered fitness was submitted to variance analysis, and if significant (P &lt; 0.05), the Scott-Knott test (5%) was applied. In the second experiment, three rations were formulated: one by the Simplex method, and two employing the GA. The feeds formulated with the GA used the parameters of population size, parent selection method, and number of generations, defined in experiment 1. The results obtained by the GA provided feeds that exhibited a mean difference in nutritional requirements of 0.34% for the ration formulated by the roulette-wheel method and 0.16% for the tournament selection of three technique. These differences are considered small and may not impact on animal performance and carcass characteristics. The variation regarding the GA results, given its heuristic attribute, was tested in experiment 3 using 100 repetitions of each method of parent selection, employing the same parameters regarding population size and number of generations of the rations formulated in experiment 2. The obtained results demonstrate low data dispersion. In conclusion, the GA is an efficient optimization strategy for the formulation of broiler chicken feeds, since it approximates the exact fulfillment of the nutritional requirement, with small variation, and with minimum cost.
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Vernersson, Ante. "Adaptive Backprojection : Developing a simple reconstruction algorithm." Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-34098.

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This group project aims to investigate the possibility ofconstructing a prototype micro-CT-scanner, hopefullyfurthering the advancement in the field of small CT-scanners,with the ultimate goal to provide a structure useable in anambulance, to scan and send images to the hospital, so thattreatment can commence directly upon arrival.This report deals with the matter of reconstructing the takenimages to construct a three-dimensional model of thescanned object. An algorithm is developed in a mannerunderstandable to those not familiar with traditionalreconstruction techniques, simplifying the understanding ofCT backprojection while also providing a useful algorithm touse along with the scanner setup. The working principles ofthe reconstruction algorithm are explained along with itsdevelopment process, and the project ends with clear resultsin the form of an “Adaptive Backprojection” algorithm.
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Books on the topic "Algorithme du simplexe"

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Orlin, James B. Polynomial dual network simplex algorithms. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1991.

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Orlin, James B. Polynomial dual network simplex algorithms. Dept. of Computer Science, Stanford University, 1991.

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Currie, James D. The complexity of the simplex algorithm. Carleton University, Mathematics and Statistics, 1985.

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The simple genetic algorithm: Foundations and theory. MIT Press, 1999.

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Computational techniques of the simplex method. Kluwer Academic Publishers, 2003.

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Iwata, Satoru. A simple combinatorial algorithm for submodular function minimization. Kyōto Daigaku Sūri Kaiseki Kenkyūjo, 2008.

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Ahuja, Ravindra K. A fast and simple algorithm for the maximum flow problem. Sloan School of Management, Massachusetts Institute of Technology, 1988.

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Ahuja, Ravindra K. A fast and simple algorithm for the maximum flow problem. Sloan School of Management, Massachusetts Institute of Technology, 1987.

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Ahuja, Ravindra K. Improved primal simplex algorithms for shortest path, assignment and minimum cost flow problems. Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1988.

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Riefenberg, Jennifer S. A simplex-method-based algorithm for determining the source location of microseismic events. Dept. of the Interior, 1989.

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Book chapters on the topic "Algorithme du simplexe"

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Padberg, Manfred. "Simplex Algorithms." In Linear Optimization and Extensions. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-12273-0_5.

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Alevras, Dimitris, and Manfred W. Padberg. "Simplex Algorithms." In Linear Optimization and Extensions. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56628-8_5.

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Borgwardt, Karl Heinz. "Simplex-Algorithmus." In Aufgabensammlung und Klausurentrainer zur Optimierung. Vieweg+Teubner, 2010. http://dx.doi.org/10.1007/978-3-8348-9354-3_6.

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Numata, Kazumiti, and Takeshi Tokuyama. "Splitting a configuration in a simplex." In Algorithms. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52921-7_92.

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Strayer, James K. "The Simplex Algorithm." In Linear Programming and Its Applications. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-1009-2_3.

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Cottle, Richard W., and Mukund N. Thapa. "THE SIMPLEX ALGORITHM." In Linear and Nonlinear Optimization. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7055-1_3.

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Karloff, Howard. "The Simplex Algorithm." In Linear Programming. Birkhäuser Boston, 2009. http://dx.doi.org/10.1007/978-0-8176-4844-2_2.

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Martin, Richard Kipp. "The Simplex Algorithm." In Large Scale Linear and Integer Optimization: A Unified Approach. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4975-8_5.

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Gass, Saul I., and Carl M. Harris. "Network simplex algorithm." In Encyclopedia of Operations Research and Management Science. Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_666.

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Gass, Saul I., and Carl M. Harris. "Simplex method (algorithm)." In Encyclopedia of Operations Research and Management Science. Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_953.

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Conference papers on the topic "Algorithme du simplexe"

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Trabia, Mohamed B., and Xiao Bin Lu. "A Fuzzy Adaptive Simplex Search Optimization Algorithm." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/dac-8586.

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Abstract Optimization algorithms usually use fixed parameters that are empirically chosen to reach the minimum for various objective functions. This paper shows how to incorporate fuzzy logic in optimization algorithms to make the search adaptive to various objective functions. This idea is applied to produce a new algorithm for minimization of a function of n variables using an adaptive form of the simplex method. The search starts by generating a simplex with n+1 vertices. The algorithm replaces the point with the highest function value by a new point. This process comprises reflecting the point with the highest function value in addition to expanding or contracting the simplex using fuzzy logic controllers whose inputs incorporate the relative weights of the function values at the simplex points. The efficiency of the algorithm is studied using a set of standard minimization test problems. This algorithm generally results in a faster convergence toward the minimum. The algorithm is also applied successfully to two engineering design problems.
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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.

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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 &amp; 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.
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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.

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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.
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Azad, Arman, and Jorn Hansen. "Method of Regular Simplexes: A Difference-Assisted Simplex-Based Search Algorithm." In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-6022.

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Ladkany, George S., and Mohamed B. Trabia. "A Hybrid Biomimetic Genetic Algorithm Using a Local Fuzzy Simplex Search." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-29085.

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This paper presents a hybrid genetic algorithm that expands upon the previously successful approach of twinkling genetic algorithm (TGA) by incorporating a highly efficient local fuzzy-simplex search within the algorithm. The TGA was in principle a bio-mimetic algorithm that introduced a controlled deviation from a typical GA method, by not requiring that every genevariable of an offspring be the result of a crossover. Instead, twinkling allowed the genetic information of the randomly chosen gene locations to be directly passed on from one parent, which was shown to increase the likelihood of survival of a successful gene value within the offspring, rather than requiring it to be blended. The twinkling genetic algorithms proved highly effective at locating exact global optimum with a competitive rate of convergence for a wide variety of benchmark problems. In this work, it is proposed to couple the TGA with a fuzzy simplex local search to increase the rate of convergence of the algorithm. The proposed algorithm is tested using common mathematical and engineering design benchmark problems. Comparison of the results of this algorithm with earlier algorithms is presented.
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Bei, Xiaohui, Youming Qiao, and Shengyu Zhang. "Networked Fairness in Cake Cutting." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/508.

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We introduce a graphical framework for fair division in cake cutting, where comparisons between agents are limited by an underlying network structure. We generalize the classical fairness notions of envy-freeness and proportionality in this graphical setting. An allocation is called envy-free on a graph if no agent envies any of her neighbor's share, and is called proportional on a graph if every agent values her own share no less than the average among her neighbors, with respect to her own measure. These generalizations enable new research directions in developing simple and efficient algorithms that can produce fair allocations under specific graph structures. On the algorithmic frontier, we first propose a moving-knife algorithm that outputs an envy-free allocation on trees. The algorithm is significantly simpler than the discrete and bounded envy-free algorithm introduced in [Aziz and Mackenzie, 2016] for compete graphs. Next, we give a discrete and bounded algorithm for computing a proportional allocation on transitive closure of trees, a class of graphs by taking a rooted tree and connecting all its ancestor-descendant pairs.
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Showalter, Mark, Dennis Hong, and Daniel Larimer. "Development and Comparison of Gait Generation Algorithms for Hexapedal Robots Based on Kinematics With Considerations for Workspace." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49616.

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This paper explores the interdependance of walking algorithm and limb workspace for the Multi-Appendage Robotic System (MARS). While MARS is a hexapedal robot, the tasks of defining the workspace and walking agorthm for all six limbs can be abstracted to a single limb using the constraint of a tripedal statically stable gait. Thus, by understanding the behavior of an individual limb, two walking algorithms have been developed which allow MARS to walk on level terain. Both algorithms are adaptive in that they continously update based on control inputs. The differences between the two algorithms is that they were developed for different limb workspaces. The simpler algorithm developed for a 2D workspace was implemented, resulting in smooth gait generation with near instantaneous response to control input. This accomplishment demonstrates the feasibility of implementing a more sophisticated algorithem which allows for inputs of: x and y velocity, walking height, yaw, pitch and roll. This algorithm uses a 3D workspace developed to afford near maximum step length.
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Van der Velden, Alex, and David Kokan. "The Synaps Pointer Optimization Engine." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34403.

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This paper describes a innovative optimization algorithm called Pointer. The Pointer software consists of a complementary set of optimization algorithms: linear simplex, sequential quadratic programming (SQP), downhill simplex, and genetic algorithms. Pointer can efficiently solve a wide range of problems in a fully automatic manner due to a special automatic control algorithm. The goal of the Pointer software is to make optimization more accessible to non-expert users without sacrificing performance.
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Hunsberger, Luke, and Roberto Posenato. "Simpler and Faster Algorithm for Checking the Dynamic Consistency of Conditional Simple Temporal Networks." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/184.

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Recent work on Conditional Simple Temporal Networks (CSTNs) has focused on checking the dynamic consistency (DC) property assuming that execution strategies can react instantaneously to observations. Three alternative semantics---IR-DC, 0-DC, and π-DC---have been presented. The most practical DC-checking algorithm for CSTNs has only been analyzed with respect to the IR-DC semantics, while the 0-DC semantics was shown to have a serious flaw that the π-DC semantics fixed. Whether the IR-DC semantics had the same flaw and, if so, what the consequences would be for the DC-checking algorithm remained open questions. This paper (1) shows that the IR-DC semantics is also flawed; (2) shows that one of the constraint-propagation rules from the IR-DC-checking algorithm is not sound with respect to the IR-DC semantics; (3) presents a simpler algorithm, called the π-DC-checking algorithm; (4) proves that it is sound and complete with respect to the π-DC semantics; and (5) empirically evaluates the new algorithm.
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Scott, Eric O., and Kenneth A. De Jong. "Understanding Simple Asynchronous Evolutionary Algorithms." In FOGA '15: Foundations of Genetic Algorithms XIII. ACM, 2015. http://dx.doi.org/10.1145/2725494.2725509.

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Reports on the topic "Algorithme du simplexe"

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Orlin, James B., Serge A. Plotkin, and Eva Tardos. Polynomial Dual Network Simplex Algorithms. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada254340.

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Dennis, Jr, Woods J. E., and Daniel J. Optimization on Microcomputers: The Nelder-Mead Simplex Algorithm. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada453814.

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Ellinger, Carola. Simple Algorithms for a Physics Code Base. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1643902.

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Crispin, M. i;unicode-casemap - Simple Unicode Collation Algorithm. RFC Editor, 2007. http://dx.doi.org/10.17487/rfc5051.

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Goldberg, Andrew V., Michael D. Grigoriadis, and Robert E. Tarjan. Efficiency of the Network Simplex Algorithm for the Maximum Flow Problem. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada214691.

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Chen, Hsin-Der, P. M. Pardalos, and M. A. Saunders. The simplex algorithm with a new primal and dual pivot rule. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/10179889.

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Altshuler, Edward E., David E. Goldberg, Robert Mailloux, Terry H. O'Donnell, and Scott G. Santarelli. Military Antenna Design Using Simple and Competent Genetic Algorithms. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada430651.

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Tseng, Paul. A Very Simple Polynomial-Time Algorithm for Linear Programming. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada202502.

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Deller, Jr, Hunt J. R., and S. D. A Simple 'Linearized' Learning Algorithm Which Outperforms Back-Propagation. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada249697.

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Kanungo, T., D. M. Mount, N. S. Netanyahu, C. Piatko, R. Silverman, and A. Y. Wu. The Analysis of a Simple k-Means Clustering Algorithm. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada458738.

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