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1

MARTINS, ROBERTO CINTRA. "SHOR S FACTORING ALGORITHM." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2018. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35511@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
A dissertação apresenta detalhadamente o algoritmo de fatoração de Shor, tanto em termos de sua execução passo a passo como mediante sua representação em forma de circuito, abordando aspectos tanto de sua parte clássica como de sua parte quântica. Inicialmente são apresentados aspectos de teoria dos números indispensáveis para a compreensão do algoritmo e em seguida são desenvolvidos conceitos e propriedades de mecânica quântica e de informação quântica pertinentes. Em atenção ao caráter eminentemente estocástico do algoritmo realiza-se um estudo de sua fonte estocástica e demonstram-se os principais teoremas que embasam a avaliação de sua probabilidade de sucesso. Desenvolvem-se exemplos de simulação clássica do algoritmo. Finalmente, a eficiência do algoritmo de fatoração de Shor é comparada com a de algoritmos clássicos.
The dissertation presents in detail Shor s factoring algorithm, including its execution step by step and its representation in the form of a circuit, addressing aspects of both its classical and its quantum parts. Aspects of number theory indispensable to understand the algorithm are presented, followed by a development of concepts and properties of quantum mechanics and quantum information. Considering the eminently stochastic character of the algorithm, a study of its stochastic source is carried out and the main theorems that support the evaluation of its probability of success are proved. Examples of classical simulation of the algorithm are developed. Finally, the efficiency of Shor s factoring algorithm is compared with that of classical algorithms.
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2

Nwaokocha, Martyns. "Shorův algoritmus v kvantové kryptografii." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-445457.

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Kryptografie je velmi důležitým aspektem našeho každodenního života, protože poskytuje teoretický základ informační bezpečnosti. Kvantové výpočty a informace se také stávají velmi důležitou oblastí vědy kvůli mnoha aplikačním oblastem včetně kryptologie a konkrétněji v kryptografii veřejných klíčů. Obtížnost čísel do hlavních faktorů je základem některých důležitých veřejných kryptosystémů, jejichž klíčem je kryptosystém RSA . Shorův kvantový faktoringový al-goritmus využívá zejména kvantový interferenční účinek kvantového výpočtu k faktorovým semi-prime číslům v polynomiálním čase na kvantovém počítači. Ačkoli kapacita současných kvantových počítačů vykonávat Shorův algoritmus je velmi omezená, existuje mnoho rozsáhlých základních vědeckých výzkumů o různých technikách optimalizace algoritmu, pokud jde o faktory, jako je počet qubitů, hloubka obvodu a počet bran. v této práci jsou diskutovány, analyzovány a porovnávány různé varianty Shorova factoringového algoritmu a kvantových obvodů. Některé varianty Shorova algoritmu jsou také simulované a skutečně prováděné na simulátorech a kvantových počítačích na platformě IBM QuantumExperience. Výsledky simulace jsou porovnávány z hlediska jejich složitosti a míry úspěšnosti. Organizace práce je následující: Kapitola 1 pojednává o některých klíčových historických výsledcích kvantové kryptografie, uvádí problém diskutovaný v této práci a představuje cíle, kterých má být dosaženo. Kapitola 2 shrnuje matematické základy kvantového výpočtu a kryptografie veřejných klíčů a popisuje notaci použitou v celé práci. To také vysvětluje, jak lze k rozbití kryptosystému RSA použít realizovatelný algoritmus pro vyhledávání objednávek nebo factoring. Kapitola 3 představuje stavební kameny Shorova algoritmu, včetně kvantové Fourierovy transformace, kvantového odhadu fází, modulární exponentiace a Shorova algoritmu. Zde jsou také uvedeny a porovnány různé varianty optimalizace kvantových obvodů. Kapitola 4 představuje výsledky simulací různých verzí Shorova algoritmu. V kapitole 5 pojednejte o dosažení cílů disertační práce, shrňte výsledky výzkumu a nastíňte budoucí směry výzkumu.
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3

Nyman, Peter. "Representation of Quantum Algorithms with Symbolic Language and Simulation on Classical Computer." Licentiate thesis, Växjö University, School of Mathematics and Systems Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2329.

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Utvecklandet av kvantdatorn är ett ytterst lovande projekt som kombinerar teoretisk och experimental kvantfysik, matematik, teori om kvantinformation och datalogi. Under första steget i utvecklandet av kvantdatorn låg huvudintresset på att skapa några algoritmer med framtida tillämpningar, klargöra grundläggande frågor och utveckla en experimentell teknologi för en leksakskvantdator som verkar på några kvantbitar. Då dominerade förväntningarna om snabba framsteg bland kvantforskare. Men det verkar som om dessa stora förväntningar inte har besannats helt. Många grundläggande och tekniska problem som dekoherens hos kvantbitarna och instabilitet i kvantstrukturen skapar redan vid ett litet antal register tvivel om en snabb utveckling av kvantdatorer som verkligen fungerar. Trots detta kan man inte förneka att stora framsteg gjorts inom kvantteknologin. Det råder givetvis ett stort gap mellan skapandet av en leksakskvantdator med 10-15 kvantregister och att t.ex. tillgodose de tekniska förutsättningarna för det projekt på 100 kvantregister som aviserades för några år sen i USA. Det är också uppenbart att svårigheterna ökar ickelinjärt med ökningen av antalet register. Därför är simulering av kvantdatorer i klassiska datorer en viktig del av kvantdatorprojektet. Självklart kan man inte förvänta sig att en kvantalgoritm skall lösa ett NP-problem i polynomisk tid i en klassisk dator. Detta är heller inte syftet med klassisk simulering. Den klassiska simuleringen av kvantdatorer kommer att täcka en del av gapet mellan den teoretiskt matematiska formuleringen av kvantmekaniken och ett förverkligande av en kvantdator. Ett av de viktigaste problemen i vetenskapen om kvantdatorn är att utveckla ett nytt symboliskt språk för kvantdatorerna och att anpassa redan existerande symboliska språk för klassiska datorer till kvantalgoritmer. Denna avhandling ägnas åt en anpassning av det symboliska språket Mathematica till kända kvantalgoritmer och motsvarande simulering i klassiska datorer. Konkret kommer vi att representera Simons algoritm, Deutsch-Joszas algoritm, Grovers algoritm, Shors algoritm och kvantfelrättande koder i det symboliska språket Mathematica. Vi använder samma stomme i alla dessa algoritmer. Denna stomme representerar de karaktäristiska egenskaperna i det symboliska språkets framställning av kvantdatorn och det är enkelt att inkludera denna stomme i framtida algoritmer.


Quantum computing is an extremely promising project combining theoretical and experimental quantum physics, mathematics, quantum information theory and computer science. At the first stage of development of quantum computing the main attention was paid to creating a few algorithms which might have applications in the future, clarifying fundamental questions and developing experimental technologies for toy quantum computers operating with a few quantum bits. At that time expectations of quick progress in the quantum computing project dominated in the quantum community. However, it seems that such high expectations were not totally justified. Numerous fundamental and technological problems such as the decoherence of quantum bits and the instability of quantum structures even with a small number of registers led to doubts about a quick development of really working quantum computers. Although it can not be denied that great progress had been made in quantum technologies, it is clear that there is still a huge gap between the creation of toy quantum computers with 10-15 quantum registers and, e.g., satisfying the technical conditions of the project of 100 quantum registers announced a few years ago in the USA. It is also evident that difficulties increase nonlinearly with an increasing number of registers. Therefore the simulation of quantum computations on classical computers became an important part of the quantum computing project. Of course, it can not be expected that quantum algorithms would help to solve NP problems for polynomial time on classical computers. However, this is not at all the aim of classical simulation. Classical simulation of quantum computations will cover part of the gap between the theoretical mathematical formulation of quantum mechanics and the realization of quantum computers. One of the most important problems in "quantum computer science" is the development of new symbolic languages for quantum computing and the adaptation of existing symbolic languages for classical computing to quantum algorithms. The present thesis is devoted to the adaptation of the Mathematica symbolic language to known quantum algorithms and corresponding simulation on the classical computer. Concretely we shall represent in the Mathematica symbolic language Simon's algorithm, the Deutsch-Josza algorithm, Grover's algorithm, Shor's algorithm and quantum error-correcting codes. We shall see that the same framework can be used for all these algorithms. This framework will contain the characteristic property of the symbolic language representation of quantum computing and it will be a straightforward matter to include this framework in future algorithms.

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4

Drobouchevitch, Inna G. "Design and analysis of algorithms for short-route shop scheduling problems." Thesis, University of Greenwich, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285392.

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5

Blum, Christian. "Metaheuristics for Group Shop Scheduling." Doctoral thesis, Universite Libre de Bruxelles, 2002. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211345.

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6

Ta, Quang-Chieu. "Matheuristic algorithms for minimizing total tardiness in flow shop scheduling problems." Thesis, Tours, 2015. http://www.theses.fr/2015TOUR4002/document.

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Nous considérons dans cette thèse un problème d’ordonnancement de flow-shop de permutation où un ensemble de travaux doit être ordonnancé sur un ensemble de machines. Les travaux doivent être ordonnancés sur les machines dans le même ordre. L’objectif est de minimiser le retard total. Nous proposons des algorithmes heuristiques et des nouvelles matheuristiques pour ce problème. Les matheuristiques sont un nouveau type d’algorithmes approchés qui ont été proposés pour résoudre des problèmes d’optimisation combinatoire. Les méthodes importent de la résolution exacte au sein des approches (méta) heuristiques. Ce type de méthode de résolution a reçu un grand intérêt en raison de leurs très bonnes performances pour résoudre des problèmes difficiles. Nous présentons d’abord les concepts de base d’un problème d’ordonnancement. Nous donnons aussi une brève introduction à la théorie de l’ordonnancement et nous présentons un panel de méthodes de résolution. Enfin, nous considérons un problème où un flow shop de permutation à m-machine et un problème de tournées de véhicules sont intégrés, avec pour objectif la minimisation de la somme des retards. Nous proposons un codage direct d’une solution et une méthode de voisinage. Les résultats montrent que l’algorithme Tabou améliore grandement la solution initiale donnée par EDD et où chaque voyage ne délivre qu’un travail
We consider in this thesis a permutation flow shop scheduling problem where a set of jobs have to be scheduled on a set of machines. The jobs have to be processed on the machines in the same order. The objective is to minimize the total tardiness. We propose heuristic algorithms and many new matheuristic algorithms for this problem. The matheuristic methods are a new type of approximated algorithms that have been proposed for solving combinatorial optimization problems. These methods embed exact resolution into (meta)heuristic approaches. This type of resolution method has received a great interest because of their very good performances for solving some difficult problems. We present the basic concepts and components of a scheduling problem and the aspects related to these components. We also give a brief introduction to the theory of scheduling and present an overview of resolution methods. Finally, we consider a problem where m-machine permutation flow shop scheduling problem and a vehicle routing problem are integrated and the objective is to minimize the total tardiness. We introduce a direct coding for a complete solution and a Tabu search for finding a sequence and trips. The results show that the TS greatly improves the initial solution given by EDD heuristic where each trip serves only one job at a time
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7

Bandini, Michele. "Crittografia quantistica e algoritmo di Shor." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/17073/.

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In questo elaborato si cerca di dare un'idea di come funzioni un computer quantistico, portando come esempio l'Algoritmo di Shor per la fattorizzazione: si cerca di chiarirne la matematica e la fisica che vi stanno dietro e l'importanza applicativa e storica che ha avuto. Brevi cenni sull'odierna tecnologia dei calcolatori quantistici.
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8

Kugel, Felix. "Das Shor-Verfahren als stochastischer Algorithmus." [S.l.] : [s.n.], 2006. http://137.193.200.177/ediss/kugel-felix/meta.html.

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9

Weyer, Anne. "The Brute Force Algorithm." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1555605680617133.

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10

Larabi, Mohand. "Le problème de job-shop avec transport : modélisation et optimisation." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2010. http://tel.archives-ouvertes.fr/tel-00625528.

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Dans cette thèse nous nous sommes intéressés à l'extension du problème job-shop en ajoutant la contrainte du transport des jobs entre les différentes machines. Dans cette étude nous avons retenu l'existence de deux types de robots, les robots de capacité de chargement unitaire (capacité=1 veut dire qu'un robot ne peut transporter qu'un seul job à la fois) et les robots de capacité de chargement non unitaire (capacité>1 veut dire qu'un robot peut transporter plusieurs job à la fois). Nous avons traité cette extension en deux étapes. Ainsi, la première étape est consacrée au problème du job-shop avec plusieurs robots de capacité de chargement unitaire et en seconde étape en ajoutant la capacité de chargement non unitaire aux robots. Pour les deux problèmes étudiés nous avons proposé :* Une modélisation linéaire ;* Une modélisation sous forme de graphe disjonctif ;* Plusieurs heuristiques de construction de solutions ;* Plusieurs recherches locales qui améliorent les solutions obtenues ;* Utilisation des algorithmes génétiques / mémétiques comme schéma global d'optimisation ;* De nouveaux benchmarks, des résultats de test de nos approches sur nos benchmarks et ceux de la littérature et ces résultats sont commentés et comparés à ceux de la littérature. Les résultats obtenus montrent la pertinence de notre modélisation ainsi que sa qualité.
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11

Gilkinson, John C. "An expert scheduling system utilizing a genetic algorithm in solving a multi-parameter job shop problem." Ohio : Ohio University, 1999. http://www.ohiolink.edu/etd/view.cgi?ohiou1175881721.

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Thakkar, Darshan Suresh, and darshanst@gmail com. "FPGA Implementation of Short Word-Length Algorithms." RMIT University. Electrical and Computer Engineering, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080806.140908.

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Short Word-Length refers to single-bit, two-bit or ternary processing systems. SWL systems use Sigma-Delta Modulation (SDM) technique to express an analogue or multi-bit input signal in terms of a high frequency single-bit stream. In Sigma-Delta Modulation, the input signal is coarsely quantized into a single-bit representation by sampling it at a much higher rate than twice the maximum input frequency viz. the Nyquist rate. This single-bit representation is almost exclusively filtered to remove conversion quantization noise and sample decimated to the Nyquist frequency in preparation for traditional signal processing. SWL algorithms have a huge potential in a variety of applications as they offer many advantages as compared to multi-bit approaches. Features of SWL include efficient hardware implementation, increased flexibility and massive cost savings. Field Programmable Gate Arrays (FPGAs) are SRAM/FLASH based integrated circuits that can be programmed and re-programmed by the end user. FPGAs are made up of arrays of logic gates, routing channels and I/O blocks. State-of-the-art FPGAs include features such as Advanced Clock Management, Dedicated Multipliers, DSP Slices, High Speed I/O and Embedded Microprocessors. A System-on-Programmable-Chip (SoPC) design approach uses some or all the aforementioned resources to create a complete processing system on the device itself, ensuring maximum silicon area utilization and higher speed by eliminating inter-chip communication overheads. This dissertation focuses on the application of SWL processing systems in audio Class-D Amplifiers and aims to prove the claims of efficient hardware implementation and higher speeds of operation. The analog Class-D Amplifier is analyzed and an SWL equivalent of the system is derived by replacing the analogue components with DSP functions wherever possible. The SWL Class-D Amplifier is implemented on an FPGA, the standard emulation platform, using VHSIC Hardware Description Languages (VHDL). The approach is taken a step forward by adding re-configurability and media selectivity and proposing SDM adaptivity to improve performance.
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13

Vilcot, Geoffrey. "Algorithmes approchés pour des problèmes d'ordonnancement multicritères de type job shop flexible et job shop multiressource." Phd thesis, Université François Rabelais - Tours, 2007. http://tel.archives-ouvertes.fr/tel-00198068.

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Ce travail de thèse s'inscrit dans le cadre d'une collaboration industrielle avec la société Volume Software pour le développement du module d'ordonnancement du logiciel "DirectPlanning". Dans ce travail, nous étudions le problème de job shop flexible multicritère et le problème de job shop multiressource multicritère. Notre objectif est de déterminer une approximation du front de Pareto. Nous avons proposé des algorithmes de résolution approchés et plus particulièrement des algorithmes de recherche Tabou et des algorithmes génétiques. Nous avons proposé différentes versions de nos méthodes pour les deux problèmes considérés. Des expérimentations ont été réalisées et montrent les bonnes performances de nos algorithmes, à la fois d'un point de vue qualité des résultats et d'un point de vue de la rapidité des méthodes.
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14

Topalli, Ayca Kumluca. "Hybrid Learning Algorithm For Intelligent Short-term Load Forecasting." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/627505/index.pdf.

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Short-term load forecasting (STLF) is an important part of the power generation process. For years, it has been achieved by traditional approaches stochastic like time series
but, new methods based on artificial intelligence emerged recently in literature and started to replace the old ones in the industry. In order to follow the latest developments and to have a modern system, it is aimed to make a research on STLF in Turkey, by neural networks. For this purpose, a method is proposed to forecast Turkey&rsquo
s total electric load one day in advance. A hybrid learning scheme that combines off-line learning with real-time forecasting is developed to make use of the available past data for adapting the weights and to further adjust these connections according to the changing conditions. It is also suggested to tune the step size iteratively for better accuracy. Since a single neural network model cannot cover all load types, data are clustered due to the differences in their characteristics. Apart from this, special days are extracted from the normal training sets and handled separately. In this way, a solution is proposed for all load types, including working days, weekends and special holidays. For the selection of input parameters, a technique based on principal component analysis is suggested. A traditional ARMA model is constructed for the same data as a benchmark and results are compared. Proposed method gives lower percent errors all the time, especially for holiday loads. The average error for year 2002 data is obtained as 1.60%.
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Yang, Tianshu. "Electric Load Forecasting Using Long Short-term Memory Algorithm." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/6027.

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Abstract Power system load forecasting refers to the study or uses a mathematical method to process past and future loads systematically, taking into account important system operating characteristics, capacity expansion decisions, natural conditions, and social impacts, to meet specific accuracy requirements. Dependence of this, determine the load value at a specific moment in the future. Improving the level of load forecasting technology is conducive to the planned power management, which is conducive to rationally arranging the grid operation mode and unit maintenance plan, and is conducive to formulating reasonable power supply construction plans and facilitating power improvement, and improve the economic and social benefits of the system. At present, there are many methods for load forecasting. The newer algorithms mainly include the neural network method, time series method, regression analysis method, support vector machine method, and fuzzy prediction method. However, most of them do not apply to long-term time-series predictions, and as a result, the prediction accuracy for long-term power grids does not perform well. This thesis describes the design of an algorithm that is used to predict the load in a long time-series. Predict the load is significant and necessary for a dynamic electrical network. Improved the forecasting algorithm can save a ton of the cost of the load. In this paper, we propose a load forecasting model using long short-term memory(LSTM). The proposed implementation of LSTM match with the time-series dataset very well, which can improve the accuracy of convergence of the training process. We experiment with the difference time-step to expedites the convergence of the training process. It is found that all cases achieve significant different forecasting accuracy while forecasting the difference timesteps. Keywords—Load forecasting, long short-term memory, micro-grid
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Povoda, Lukáš. "Rozvrhování úkolů v logistických skladech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220620.

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The main aim of this thesis is flow shop and job shop scheduling problem in logistics warehouses. Managing and scheduling works is currently often problem. There is no simple solution due to complexity of this problem. This problem must be resolved because of a lack efficiency of work with a higher load such as during the christmas holidays. This paper describes the methods used to solve this problem focusing mainly on the use of search algorithms, evolutionary algorithms, specifically grammar guided genetic programming. This paper describes the problem of job shop scheduling on a simple theoretical example. The implemented algorithm for solving this problem was subjected to tests inspired on data from real warehouse, as well as synthetically created tests with more jobs and a greater number of workers. Synthetic tests were generated randomly. All tests were therefore run several times and the results were averaged. In conclusion of this work are presented the results of the algorithm and the optimum parameter settings for different sizes of problems and requirements for the solution. Genetic algorithm has been extended to calculate fitness of individuals with regard to number of collisions, extended to use priority rules during run of evolution, and some parts of algorithm was parallelized.
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GOLDNER, ELIANA LEITE. "EVALUATION OF A SHORT PATH ALGORITHM FOR SEISMIC HORIZON TRACKING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24300@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO
PROGRAMA DE EXCELENCIA ACADEMICA
BOLSA NOTA 10
A interpretação manual de um horizonte sísmico é um processo muito custoso em termos de tempo de trabalho do intérprete, o que incentiva a pesquisa de métodos automáticos, ou semi automáticos, de rastreamento. Dentre as propostas existentes baseadas em correlação, uma limitação conhecida é o uso de abordagens locais para definir as amostras pertencentes ao horizonte rastreado. Esse tipo de abordagem possui bom desempenho em dados onde não há a presença de falhas sísmicas, porém, nas regiões de baixa coerência, característica das regiões ruidosas ou de falhas, ao tomar uma decisão local o rastreador fica suscetível à propagação de erro. O objetivo deste trabalho é avaliar o uso de algoritmos de menor caminho em grafos para a solução do problema de rastreamento de horizontes sísmicos, afim de propor um método de caráter global que seja robusto a diferentes feições sísmicas.
The manual interpretation of a seismic horizon is a time consuming process, which drives the research for automatic or semi automatic tracking methods. Among the known propositions that use correlation, there is a common limitation: the usage of local approaches to determine which samples belong to the horizon. This kind of approach performs well in data where there are no seismi faults. However, by using only local information, it is prone to error propagation in low coherency areas, which usualy corresponds to fault regions. The goal of this work is to evaluate the performance of shortest path algorithms as a solution for the horizont tracking problem. It intends to propose a global method that is robust to different seismic features.
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Sansuke, Maranhão Watanabe Mário. "O algoritmo polinomial de Shor para fatoração em um computador quântico." Universidade Federal de Pernambuco, 2003. https://repositorio.ufpe.br/handle/123456789/7361.

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Sistemas de criptografia largamente difundidos como o RSA fundamentam a sua eficiência na suposição de que, em termos práticos, é impossível fatorar números inteiros suficientemente grandes em uma escala de tempo aceitável. Mais precisamente, não existem, até o momento, algoritmos de fatoração em tempo polinomial que possam ser implementados nos atuais computadores. Dentre os algoritmos conhecidos, o mais eficiente requer um tempo computacional de ordem exponencial na quantidade de dígitos binários do número a ser fatorado. Em 1994, baseado nos trabalhos anteriores de Benioff, Bennett, Deutsch, Feynman e Simon, dentre outros, Peter Shor apresentou um algoritmo de fatoração que requer assintoticamente uma quantidade em ordem polinomial de passos em um computador quântico para fatorar um número inteiro de tamanho arbitrário. Esse algoritmo ao invés de abordar o problema de decompor tal número em dois fatores não triviais pelo método direto de divisões sucessivas, utiliza o problema equivalente de encontrar a ordem de um certo inteiro modulo o número fatorado, onde esse inteiro é escolhido aleatoriamente relativamente primo com o número fatorado. Shor faz uso de um algoritmo quântico para calcular essa ordem. A computação quântica revela um paradigma computacional bastante adverso da computação clássica. Enquanto esta última é realizada através de operações binárias determinísticas com base na lógica booleana clássica, a computação quântica fundamenta as suas operações nos postulados que descrevem o comportamento quântico da matéria. Portanto, é probabilística no seu modus operandi. Essa diferença entre os formalismos lógicos da computação clássica e da computação quântica é um reflexo direto da natureza dos sistemas físicos que são utilizados para implementar concretamente cada uma dessas computações. Esta dissertação apresenta o algoritmo de Shor para fatoração em um computador quântico. Na seqüência, introduzimos no capítulo 1 alguns conceitos básicos da computação clássica com o objetivo de criar um ambiente de idéias favorável à apresentação da computação quântica como uma extensão, tão natural quanto possível, do modelo clássico computacional. Assim, no capítulo 2, apresentamos as bases do formalismo matemático que modela a computação quântica, atendo-nos apenas aos aspectos conceituais que são, direta ou indiretamente, aplicados na descrição do algoritmo de Shor. Os capítulos 3 e 4 são dedicados à apresentação do algoritmo de fatoração de Shor, feita em duas partes. A primeira diz respeito a parte não quântica e aborda os aspectos algébricos do algoritmo. Também é demonstrado o teorema que assegura a viabilidade probabilística da solução desse problema. No capítulo 4, apresentamos a parte quântica do algoritmo de Shor. O ponto alto da dissertação é alcançado mostrando-se como encontrar a ordem de um inteiro módulo o número a ser fatorado relativamente primo com este, conciliando o algoritmo quântico com uma interpretação clássica de seus dados de saída, mediante o uso da expansão de um número racional em frações contínuas
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19

Freitas, Adriana Xavier. "Algoritmo de Shor e sua aplicação à fatoração de números inteiros." Universidade Federal de Minas Gerais, 2010. http://hdl.handle.net/1843/EABA-85FJXP.

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Shors algorithm is a quantum algorithm that finds with high probability the order of an element $x \in Z_{N}^{*}$. One of its applications is the construction of an algorithm that finds the factors of N. In the initial chapters we approach necessary tools for the comprehension of Shors algorithm such as: modular arithmetic, algorithms, continued fractions, basic concepts of quantum computing and Fourier quantum transform. In the following chapters we present Shors algorithm an its application in factorization.
O algoritmo de Shor é um algoritmo quântico que encontra com alta probabilidade a ordem de um elemento $x \in Z_{N}^{*}$. Uma de suas aplicações é a construção de um algoritmo que encontra fatores de N. Nos capítulos iniciais abordaremos ferramentas necessárias para o entendimento do algoritmo de Shor, tais como: aritmética modular, algoritmos, frações contínuas, conceitos introdutórios de computação quântica e transformada quântica de Fourier. Nos capítulos seguintes apresentamos o algoritmo de Shor e sua aplicação á fatoração de números inteiros.
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Mohammad, Maruf H. "Blind Acquisition of Short Burst with Per-Survivor Processing (PSP)." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/46193.

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This thesis investigates the use of Maximum Likelihood Sequence Estimation (MLSE) in the presence of unknown channel parameters. MLSE is a fundamental problem that is closely related to many modern research areas like Space-Time Coding, Overloaded Array Processing and Multi-User Detection. Per-Survivor Processing (PSP) is a technique for approximating MLSE for unknown channels by embedding channel estimation into the structure of the Viterbi Algorithm (VA). In the case of successful acquisition, the convergence rate of PSP is comparable to that of the pilot-aided RLS algorithm. However, the performance of PSP degrades when certain sequences are transmitted. In this thesis, the blind acquisition characteristics of PSP are discussed. The problematic sequences for any joint ML data and channel estimator are discussed from an analytic perspective. Based on the theory of indistinguishable sequences, modifications to conventional PSP are suggested that improve its acquisition performance significantly. The effect of tree search and list-based algorithms on PSP is also discussed. Proposed improvement techniques are compared for different channels. For higher order channels, complexity issues dominate the choice of algorithms, so PSP with state reduction techniques is considered. Typical misacquisition conditions, transients, and initialization issues are reported.
Master of Science
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21

Metta, Haritha. "ADAPTIVE, MULTI-OBJECTIVE JOB SHOP SCHEDULING USING GENETIC ALGORITHMS." UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_theses/518.

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This research proposes a method to solve the adaptive, multi-objective job shop scheduling problem. Adaptive scheduling is necessary to deal with internal and external disruptions faced in real life manufacturing environments. Minimizing the mean tardiness for jobs to effectively meet customer due date requirements and minimizing mean flow time to reduce the lead time jobs spend in the system are optimized simultaneously. An asexual reproduction genetic algorithm with multiple mutation strategies is developed to solve the multi-objective optimization problem. The model is tested for single day and multi-day adaptive scheduling. Results are compared with those available in the literature for standard problems and using priority dispatching rules. The findings indicate that the genetic algorithm model can find good solutions within short computational time.
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Stein, Clifford. "Approximation algorithms for multicommodity flow and shop scheduling problems." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/12867.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1992.
Includes bibliographical references (leaves 174-179).
by Clifford Stein.
Ph.D.
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23

Czerwinski, Steven E. (Steven Edward). "Exploring the job-shop search space with genetic algorithms." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/42747.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
Includes bibliographical references (leaves 52-53).
by Steven E. Czerwinski.
M.Eng.
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24

Paschou, Michail. "ASIC implementation of LSTM neural network algorithm." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254290.

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LSTM neural networks have been used for speech recognition, image recognition and other artificial intelligence applications for many years. Most applications perform the LSTM algorithm and the required calculations on cloud computers. Off-line solutions include the use of FPGAs and GPUs but the most promising solutions include ASIC accelerators designed for this purpose only. This report presents an ASIC design capable of performing the multiple iterations of the LSTM algorithm on a unidirectional and without peepholes neural network architecture. The proposed design provides arithmetic level parallelism options as blocks are instantiated based on parameters. The internal structure of the design implements pipelined, parallel or serial solutions depending on which is optimal in every case. The implications concerning these decisions are discussed in detail in the report. The design process is described in detail and the evaluation of the design is also presented to measure accuracy and error of the design output.This thesis work resulted in a complete synthesizable ASIC design implementing an LSTM layer, a Fully Connected layer and a Softmax layer which can perform classification of data based on trained weight matrices and bias vectors. The design primarily uses 16-bit fixed point format with 5 integer and 11 fractional bits but increased precision representations are used in some blocks to reduce error output. Additionally, a verification environment has also been designed and is capable of performing simulations, evaluating the design output by comparing it with results produced from performing the same operations with 64-bit floating point precision on a SystemVerilog testbench and measuring the encountered error. The results concerning the accuracy and the design output error margin are presented in this thesis report. The design went through Logic and Physical synthesis and successfully resulted in a functional netlist for every tested configuration. Timing, area and power measurements on the generated netlists of various configurations of the design show consistency and are reported in this report.
LSTM neurala nätverk har använts för taligenkänning, bildigenkänning och andra artificiella intelligensapplikationer i många år. De flesta applikationer utför LSTM-algoritmen och de nödvändiga beräkningarna i digitala moln. Offline lösningar inkluderar användningen av FPGA och GPU men de mest lovande lösningarna inkluderar ASIC-acceleratorer utformade för endast dettaändamål. Denna rapport presenterar en ASIC-design som kan utföra multipla iterationer av LSTM-algoritmen på en enkelriktad neural nätverksarkitetur utan peepholes. Den föreslagna designed ger aritmetrisk nivå-parallellismalternativ som block som är instansierat baserat på parametrar. Designens inre konstruktion implementerar pipelinerade, parallella, eller seriella lösningar beroende på vilket anternativ som är optimalt till alla fall. Konsekvenserna för dessa beslut diskuteras i detalj i rapporten. Designprocessen beskrivs i detalj och utvärderingen av designen presenteras också för att mäta noggrannheten och felmarginal i designutgången. Resultatet av arbetet från denna rapport är en fullständig syntetiserbar ASIC design som har implementerat ett LSTM-lager, ett fullständigt anslutet lager och ett Softmax-lager som kan utföra klassificering av data baserat på tränade viktmatriser och biasvektorer. Designen använder huvudsakligen 16bitars fast flytpunktsformat med 5 heltal och 11 fraktions bitar men ökade precisionsrepresentationer används i vissa block för att minska felmarginal. Till detta har även en verifieringsmiljö utformats som kan utföra simuleringar, utvärdera designresultatet genom att jämföra det med resultatet som produceras från att utföra samma operationer med 64-bitars flytpunktsprecision på en SystemVerilog testbänk och mäta uppstådda felmarginal. Resultaten avseende noggrannheten och designutgångens felmarginal presenteras i denna rapport.Designen gick genom Logisk och Fysisk syntes och framgångsrikt resulterade i en funktionell nätlista för varje testad konfiguration. Timing, area och effektmätningar på den genererade nätlistorna av olika konfigurationer av designen visar konsistens och rapporteras i denna rapport.
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Arrieta, Aitor. "FB-Environment in Wise-Shop Floor : Algorithm parser and code generation." Thesis, Högskolan i Skövde, Forskningscentrum för Virtuella system, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-6594.

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IEC (International Electrotechnical Commission) is the authority that publishes different standards in the  fields  of  electrical  and  electronics  engineering,  to  be  used  internationally.  In  the  area  of manufacturing, it has demanded a new standard to fulfil better solutions of dynamic requirements. The  IEC  61499  redacted  by  IEC  offers  interoperability,  portability,  configurability  and  distributed control applications for manufacturing processes. However, this standard is not a replacement of IEC 61131-3,  one  of  the  most  used  standards  in  industry;  instead,  it  is  a  complement  of  it.  The  basic software units of IEC 61499 are named Function Blocks (FBs), which can be described as blocks that encapsulate functionality. By combining FBs together, it is possible to solve complex problems.   The  objective  of  this  project  (in  close  cooperation  with  another  project)  is  to  develop  a  software environment in Java language. It follows the requirements of IEC 61499, and implement a Function Block  designer  and  a  runtime  execution  environment,  as  a  part  of  an  existing  Wise-ShopFloor framework. The scope of this project covers:     FB  algorithm  editor:  Each  FB  has  one  or  more  algorithms,  which  can  be  defined  in  the algorithm editor using IEC 61131-3 or Java.     FB serialization: Opening and saving the configuration of FBs in Java Class file is one of the tasks  of  this  project.  As  soon  as  the  configuration  is  saved,  the  Java  code  of  FB  can  be generated. Java code is generated because compiled Java allows execution of FB. Saving in Java  Class  file  permits  portability,  i.e.  the  saved  configuration  can  be  opened  in  any  JVM system, and vice versa.      Case study: A simulation of an assembly station using an ABB IRB 140 robot is studied and implemented using the runtime simulator of the Java platform, in which some basic FBs have been also created in a library. This project also includes: (1) implementation of user interface and (2) FB serialization in XML. It  is  anticipated  that  the  developed  environment  will  be  able  to  save  and  open  FBs  configurations either in XML or in Java Class, following the specification of IEC 61499. It will allow portability and reusability.  Because  of  the  portability,  the  so-designed  FBs  can  be  validated  using  another  FB environment such as FBDK (Function Block Development Kit).
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Silwal, Hari. "MULTISTEP FRAMEWORK FOR SHORT-TERM LOAD FORECASTING USING MACHINE LEARNING ALGORITHM." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2312.

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Traditional forecasting approaches forecast the total system load directly without considering the individual consumer's load. With the introduction of the smart grid, lots of renewable energy resources such as wind and solar are added to the system from consumer side fluctuates the system load and makes forecasting more complex. Thus, it is necessary to forecast individual consumers load. Here, a framework is presented in which individual customer loads is forecasted rather than the system load. At first, a hierarchical cluster analysis is performed to classify daily load patterns into different groups for all the individuals. Then an association analysis is performed to determine critical influential factors that affect the load curve for given day. The next step is the application of a decision tree to establish classification rules between the different groups of the load curve and the critical influential factors. Then, appropriate forecasting models are chosen for different load patterns and the individual load is forecasted. Finally, the forecasted total system load is obtained through an aggregation of an individual load forecasting results. The relative error of forecasting the system load using this framework is compared with the relative errors using SVM regression and this framework had better accuracy. This framework is also used for forecasting the power output of the renewable generation. Also, the results of the day ahead forecast of system load and renewable generation is used for economic power scheduling for the microgrid and peak shaving for the utilities.
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27

Yang, Fengyu, and 楊丰羽. "Machine-order search space for job-shop scheduling." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B31246205.

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28

Al-Hinai, Nasr. "OPTIMIZING THE FLEXIBLE JOB-SHOP SCHEDULING PROBLEM USING HYBRIDIZED GENETIC ALGORITHMS." Flexible Services and Manufacturing Journal, 2011. http://hdl.handle.net/1993/4955.

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Flexible job-shop scheduling problem (FJSP) is a generalization of the classical job-shop scheduling problem (JSP). It takes shape when alternative production routing is allowed in the classical job-shop. However, production scheduling becomes very complex as the number of jobs, operations, parts and machines increases. Until recently, scheduling problems were studied assuming that all of the problem parameters are known beforehand. However, such assumption does not reflect the reality as accidents and unforeseen incidents happen in real manufacturing systems. Thus, an optimal schedule that is produced based on deterministic measures may result in a degraded system performance when released to the job-shop. For this reason more emphasis is put towards producing schedules that can handle uncertainties caused by random disruptions. The current research work addresses solving the deterministic FJSP using evolutionary algorithm and then modifying that method so that robust and/or stable schedules for the FJSP with the presence of disruptions are obtained. Evolutionary computation is used to develop a hybridized genetic algorithm (hGA) specifically designed for the deterministic FJSP. Its performance is evaluated by comparison to performances of previous approaches with the aid of an extensive computational study on 184 benchmark problems with the objective of minimizing the makespan. After that, the previously developed hGA is modified to find schedules that are quality robust and/or stable in face of random machine breakdowns. Consequently, a two-stage hGA is proposed to generate the predictive schedule. Furthermore, the effectiveness of the proposed method is compared against three other methods; two are taken from literature and the third is a combination of the former two methods. Subsequently, the hGA is modified to consider FJSP when processing times of some operations are represented by or subjected to small-to-medium uncertainty. The work compares two genetic approaches to obtain predictive schedule, an approach based on expected processing times and an approach based on sampling technique. To determine the performance of the predictive schedules obtained by both approaches with respect to two types of robustness, an experimental study and Analysis of Variance (ANOVA) are conducted on a number of benchmark problems.
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29

Gandhi, Sachin. "Learning from a Genetic Algorithm with Inductive Logic Programming." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1125511501.

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30

Schilling, Gordian Hansjoerg. "Algorithms for short-term and periodic process scheduling and rescheduling." Thesis, Imperial College London, 1998. http://hdl.handle.net/10044/1/7696.

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31

Mok, Esmond Chi Ming. "A new ambiguity function algorithm for short baseline GPS engineering surveying applications." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318165.

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32

Feng, Wenlan. "Modelling market demand and manufacturing response using genetic algorithms." Thesis, Glasgow Caledonian University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361094.

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33

Hasan, S. M. Kamrul Engineering &amp Information Technology Australian Defence Force Academy UNSW. "Evolutionary algorithms for solving job-shop scheduling problems in the presence of process interruptions." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43768.

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In this thesis, the Job Shop Scheduling Problem (JSSP) is the problem of interest. The classical JSSP is well-known as an NP-hard problem. Although with current computational capabilities, the small problems are solvable using deterministic methods, it is out of reach when they are larger in size. The complexity of JSSP is further increased when process interruptions, such as machine breakdown and/or machine unavailability, are introduced. Over the last few decades, several stochastic algorithms have been proposed to solve JSSPs. However, none of them are suitable for all kinds of problems. Genetic and Memetic algorithms have proved their effectiveness in these regards, because of their diverse searching behavior. In this thesis, we have developed one genetic algorithm and three different Memetic Algorithms (MAs) for solving JSSPs. Three priority rules are designed, namely partial re-ordering, gap reduction and restricted swapping, and these have been used as local search techniques in designing our MAs. We have solved 40 well-known benchmark problems and compared the results obtained with some of the established algorithms available in the literature. Our algorithm clearly outperforms those established algorithms. For better justification of the superiority of MAs over GA, we have performed statistical significance testing (Student's t-test). The experimental results show that MA, as compared to GA, not only significantly improves the quality of solutions, but also reduces the overall computation. We have extended our work by proposing an improved local search technique, shifted gap-reduction (SGR), which improves the performance of MAs when tested with the relatively difficult test problems. We have also modified the new algorithm to accommodate JSSPs with machine unavailability and also developed a new reactive scheduling technique to re-optimize the schedule after machine breakdowns. We have considered two scenarios of machine unavailability. Firstly, where the unavailability information is available in advance (predictive), and secondly, where the information is known after a real breakdown (reactive). We show that the revised schedule is mostly able to recover if the interruptions occur during the early stages of the schedules. We also confirm that the effect of a single continuous breakdown has more impact compared to short multiple breakdowns, even if the total durations of the breakdowns are the same. Finally, for convenience of implementation, we have developed a decision support system (DSS). In the DSS, we have built a graphical user interface (GUI) for user friendly data inputs, model choices, and output generation. This DSS tool will help users in solving JSSPs without understanding the complexity of the problem and solution approaches, as well as will contribute in reducing the computational and operational costs.
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34

Shah, Nihar. "Using Distributed Computing To Improve The Performance Of Genetic Algorithms For Job Shop Scheduling Problems." Ohio University / OhioLINK, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1103232246.

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35

Vasquez, Julio Cesar Delgado. "Programação de tarefas em um ambiente flow shop com m máquinas para a minimização do desvio absoluto total de uma data de entrega comum." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-11122017-123449/.

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Neste trabalho abordamos o problema de programação de tarefas em um ambiente flow shop permutacional com mais de duas máquinas. Restringimos o estudo para o caso em que todas as tarefas têm uma data de entrega comum e restritiva, e onde o objetivo é minimizar a soma total dos adiantamentos e atrasos das tarefas em relação a tal data de entrega. É assumido também um ambiente estático e determinístico. Havendo soluções com o mesmo custo, preferimos aquelas que envolvem menos tempo de espera no buffer entre cada máquina. Devido à dificuldade de resolver o problema, mesmo para instâncias pequenas (o problema pertence à classe NP-difícil), apresentamos uma abordagem heurística para lidar com ele, a qual está baseada em busca local e faz uso de um algoritmo linear para atribuir datas de conclusão às tarefas na última máquina. Este algoritmo baseia-se em algumas propriedades analíticas inerentes às soluções ótimas. Além disso, foi desenvolvida uma formulação matemática do problema em programação linear inteira mista (PLIM) que vai permitir validar a eficácia da abordagem. Examinamos também o desempenho das heurísticas com testes padrões (benchmarks) e comparamos nossos resultados com outros obtidos na literatura.
In this work we approach the permutational flow shop scheduling problem with more than two machines. We restrict the study to the case where all the jobs have a common and restrictive due date, and where the objective is to minimize the total sum of the earliness and tardiness of jobs relative to the due date. A static and deterministic environment is also assumed. If there are solutions with the same cost, we prefer those that involve less buffer time between each machine. Due to the difficulty of solving the problem, even for small instances (the problem belongs to the NP-hard class), we present a heuristic approach to dealing with it, which is based on local search and makes use of a linear algorithm to assign conclusion times to the jobs on the last machine. This algorithm is based on some analytical properties inherent to optimal solutions. In addition, a mathematical formulation of the problem in mixed integer linear programming (MILP) was developed that will validate the effectiveness of the approach. We also examined the performance of our heuristics with benchmarks and compared our results with those obtained in the literature.
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36

Fanti, Gioele. "Algoritmo di schedulazione per il problema di Job-Shop." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22178/.

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37

Raveendran, Nithin. "A Modified Sum-Product Algorithm over Graphs with Short Cycles." Thesis, 2015. http://etd.iisc.ernet.in/2005/3847.

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We investigate into the limitations of the sum-product algorithm for binary low density parity check (LDPC) codes having isolated short cycles. Independence assumption among messages passed, assumed reasonable in all configurations of graphs, fails the most in graphical structures with short cycles. This research work is a step forward towards understanding the effect of short cycles on error floors of the sum-product algorithm. We propose a modified sum-product algorithm by considering the statistical dependency of the messages passed in a cycle of length 4. We also formulate a modified algorithm in the log domain which eliminates the numerical instability and precision issues associated with the probability domain. Simulation results show a signal to noise ratio (SNR) improvement for the modified sum-product algorithm compared to the original algorithm. This suggests that dependency among messages improves the decisions and successfully mitigates the effects of length-4 cycles in the Tanner graph. The improvement is significant at high SNR region, suggesting a possible cause to the error floor effects on such graphs. Using density evolution techniques, we analysed the modified decoding algorithm. The threshold computed for the modified algorithm is higher than the threshold computed for the sum-product algorithm, validating the observed simulation results. We also prove that the conditional entropy of a codeword given the estimate obtained using the modified algorithm is lower compared to using the original sum-product algorithm.
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Kugel, Felix [Verfasser]. "Das Shor-Verfahren als stochastischer Algorithmus / Felix Kugel." 2006. http://d-nb.info/982288166/34.

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Soares, Sophia de Queiroz. "Escalonamento da produção num sistema job-shop flexível: aplicação ao fabrico de pavimentos de madeira." Master's thesis, 2021. http://hdl.handle.net/10316/95536.

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Dissertação de Mestrado em Engenharia e Gestão Industrial apresentada à Faculdade de Ciências e Tecnologia
This work is based on a curricular internship at the startup SimpleAxis, in Portugal, as part of the Masters in Industrial and Management Engineering at the University of Coimbra. Its main objective is to propose a solution related to the production scheduling of Castro Wood Floors enterprise, in order to minimize the makespan and the tardiness in deliveries in order to optimize the production process creating new opportunities of development to the company.In this sense, initially, a detailed characterization of the problem and of its restrictions was carried out to make it possible to look at the theoretical framework searching for the most suitable method to solve it.In this context, after analyzing several methods, seeing the most used and recurring in the literature, it was found out that the creation of a genetic algorithm would be an efficient method to solve the type of problem to be tackled in the environment of a flexible job shop.The model was implemented in Python programming language and tested to find the parameters that would achieve the best results for different instances. The best results were compared with those obtained by the algorithm used by SimpleAxis, to validate the capacity of the developed model.The comparison between the two algorithms, led to the conclusion that the model presented in this paper is efficient and not only produced better results than those achieved by SimpleAxis, but also ran in shorter computing time, meeting the initially proposed goals.
O trabalho desenvolvido nesta dissertação segue um estágio curricular na startup SimpleAxis, em Portugal, inserido no Mestrado em Engenharia e Gestão Industrial da Universidade de Coimbra. O seu objetivo principal é propor uma solução para escalonar as encomendas da empresa Castro Wood Floors, minimizando o makespan e os atrasos nas entregas, de forma a otimizar a o processo de produção criando novas oportunidade de desenvolvimento para a empresa, uma vez que Deste modo, inicialmente foi feita a caracterização detalhada do problema e das suas restrições e, a partir disso, foi possível direcionar o enquadramento teórico em busca do método mais adequado para solucioná-lo. Neste contexto, e após a análise dos vários métodos possíveis, dos mais utilizados e recorrentes na literatura, verificou-se que a criação de um algoritmo genético seria um método eficaz para resolver o tipo de problema em questão que se enquadra num job shop flexível.A implementação do modelo foi elaborada em linguagem de programação Python e testada para que se pudessem encontrar os parâmetros que trouxessem os melhores resultados para diferentes instâncias. Os melhores resultados foram analisados e comparados com os resultados obtidos pelo algoritmo feito pela startup SimpleAxis, para validar a capacidade do modelo desenvolvido.A partir desta comparação, foi possível concluir que o modelo criado é eficiente e não só gerou resultados melhores do que os alcançados pela SimpleAxis, como também o fez com tempos de computação menores tendo, portanto, alcançado os objetivos inicialmente propostos.
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40

Heng-Lei, Su, and 蘇恆磊. "Genetic Algorithms for Job-Shop Scheduling." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/23996197435893773713.

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Abstract:
碩士
國立海洋大學
系統工程暨造船學系
90
Abstract The job-shop scheduling problem is an important problem in the operation production management. During the last few decades, an efficient algorithm hasn’t been found yet for optimizing it in polynomial time. Based on the genetic algorithms is used to solve job-shop scheduling problem in this thesis. Firstly, to describe operation process, limits, performance, and the rule on dispatch in the job-shop scheduling problem. Secondly, to introduce the basic framework and important parameters such as crossover rate, mutation rate and population in genetic algorithms. According the genetic algorithm with three different crossover mechanisms such as partial-mapped crossover, one-point crossover, job-based order crossover, a program has been complemented in Fortran 90.The program is verified through four bench-mark instances of the job-shop scheduling problem having minizing makespan from paper by D. C. Mattfeld and R. J. M. Vaessens. Finally, the influence of the parameters in three genetic algorithms in this thesis on the makespan for the job-shop scheduling problems are studied and discussed.
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41

Chen, Yi-Shin, and 陳宜欣. "A Natural Genetic Algorithm for Job Shop Problem." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/06795599174634190358.

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42

Zheng, Jie-Ting, and 鄭价廷. "Applications of Genetic Algorithm to Job-Shop Scheduling." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/96943505372410130410.

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Abstract:
碩士
國立高雄第一科技大學
機械與自動化工程所
90
In this thesis, we confer using Genetic Algorithm to improve the scheduling of production plan about a job-shop scheduling problem. How to shorten total working time of production scheduling is a goal of research in the thesis. In the thesis, we research in two directions: (1) We discuss the result with using differential GA operators, and observe the influence of differential operators for the purpose of getting the best operation mold, which tends to optimal solution more. For selecting the parameter of genetic algorithm, we use Taguchi method to find the optimal parameter combination, and compare each scheduling result to prove that our way can slash total working time of production scheduling exactly. Consequentially, we successfully apply genetic algorithm to the production flow chart in the Job Shop Scheduling. (2) Now most scheduling of die industry are used by the artificial way or built by professional experience in the actual application. These ways are inefficient, waste time and manpower or can’t reach desirable result for the condition that businesses want to raise competitiveness nowadays. To solving this problem, we cooperate with the famous national research center, Metal Industries Research & Development Center, in the actual application of the thesis. We combine the MIS system of factory from Metal Industries Research & Development Center (for short: E-Pass) with the program based on the genetic algorithm theory, and think about the efficiency of time and manpower. To production scheduling in the die industry, we have developed an effective method, which reach the goal that genetic algorithm can combine with the actual application.
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43

Hsiao, Yi-Mei, and 蕭義梅. "Application of Genetic Algorithm in Job-Shop Scheduling." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/44570963801521937844.

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Abstract:
碩士
元智大學
工業工程研究所
87
In factory, it is an important problem for scheduling rapidly, and genetic algorithm is a popular method to solve the NP-hard scheduling problem. In tradition, using genetic algorithm to solve the problem needs a long time, but ''time'' is the most important problem in scheduling. This research intends to how to use the character of genetic algorithm to escape the trap in local solution, and exclude the long time of evolution from the genetic algorithm, then get the better solution in short time. In this research, we develop a combination of using crossover, and mutation rate, to derive the solution fast and better.
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44

Liu, Chung-Yang, and 劉忠陽. "Flexible Flow Shop Scheduling: Algorithm Design and Application." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/47483807357045202753.

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博士
國立臺灣大學
電機工程學研究所
88
This thesis presents a Lagrangian relaxation-based approach for production scheduling of flexible flow shops where backup and sequence-dependent setup effects (time and cost) are significant. It is well known as an NP-hard problem. Backup machine effects are modeled as using alternative machines with prioritized processing cost. In the presence of setup effects, setup status of a machine must be scheduled in accordance with individual part production schedules. The scheduling problem is formulated as a separable integer programming problem with capacity constraints among production flows of different parts and synchronization constraints between part production and machine usage scheduling variables. Lagrangian relaxation is then applied to capacity and synchronization constraints. The scheduling problem is decomposed into two classes of subproblems: part production and machine scheduling subproblems. In these subproblems, there are network flow structures in equality constraints describing production flow balance and machine status change. Our iterative solution algorithm applies a minimum cost network flow algorithm to solve individual subproblems and adopts an efficient surrogate subgradient method of Luh et al., (1997), to optimize Lagrangian multipliers. A machine availability-searching heuristic finally adjusts the solution to satisfy all capacity and synchronization constraints by exploiting the network structure, economic interpretation of Lagrangian multipliers and the slack time policy. Numerical results of 16 cases, each having 20 test problems, demonstrate that differences between the schedules obtained by our approach and the true optima are on average within 15%. CPU times spent are all less than 17 minutes on a Pentium-II personal computer. Among the problem dimension factors, the number of part types has the most significant effect on both optimality and computation efficiency. Application of the methodology to daily scheduling of a realistic integrated circuit testing facility of 30 machines takes about 6 minutes of CPU time to generate a near-optimal solution. It is also demonstrated that our algorithm can set up backup machines when customer’s due time is tight. The resulted schedule of this methodology has many potential applications. It provides the guideline to decide the batch size, to estimate the capacity consuming, to prepare machines setting up and to plan the preventative maintenance.
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45

Yang, Po-Tung, and 楊博棟. "Fuzzy Clustering Algorithm on Short Time Series Data." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/2347bj.

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碩士
中原大學
數學研究所
103
In this thesis, we propose Alternative Fuzzy Short Times Series Clustering Algorithm (A-FSTS). This thesis was to observe whether the new algorithm is better than Fuzzy Short Time Series Clustering Algorithm [3]. We using Fuzzy Short Time Series Clustering Algorithm (FSTS) [3] for Short Time Series data with outliers have some problem and the classification results are incorrect, because Fuzzy Short Time Series Clustering Algorithm [3] is based on Fuzzy C-Means Algorithm (FCM). We want to improve this problem, So we will combine distance of Short Time Series [3] and Alternative Fuzzy C-Means (AFCM) [4] as the Alternative Fuzzy Short Time Series Clustering Algorithm. This algorithm based on the Alternative Fuzzy C-Mean Algorithm, Therefore, this algorithm is not affected outliers, and improve the classification results.
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Yen, Nguyen Thi Hong, and 阮氏紅燕. "A VND ALGORITHM FOR JOB SHOP SCHEDULING PROBLEM." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/bvpmk6.

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碩士
元智大學
工業工程與管理學系
106
In this study, we consider the scheduling problem for job shop environment with the objective to minimize the makespan. Variable neighborhood descent (VND) algorithm with two versions VNDI and VNDII is proposed to solve the problem. Besides, two simple neighborhood structures based on critical operation concept are generated to be implemented with VND algorithm. Preliminary test is performed to evaluate performance of two versions of VND and the obtained results indicates that VNDI outperforms VNDII with better solution and shorter computational time. Computational tests are carried out on 45 well-known instances applying VNDI and the results are compared with the benchmark solutions and with several algorithms from other published works, in order to measure the performance of the proposed algorithm. Computational results show that VNDI is effective to find optimal or near-optimal solutions of most of the tested instances in reasonable execution time. Apart from this, VNDI is proved to perform better for rectangular instances or instances for which the number of jobs is much larger than the number of machines, than the square instances.
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Panto, Frans Januar, and 潘英發. "A job-shop scheduling algorithm based on hybrid bees algorithm combined with tabu search." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/98841233860316804705.

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碩士
國立臺灣科技大學
資訊工程系
98
The job-shop scheduling problem is one of the most NP-Hard problems and has attracted many researchers to develop new algorithm based on heuristic or meta-heuristic approach. Many algorithms based on Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization have been proposed to solve it, respectively but the results are still not yet satisfactory. In this paper we proposed a new algorithm based on bees algorithm which is very good for discrete optimization problem; furthermore, the results are optimized with the famous tabu search for local search to improve the results. The robustness, efficiency, and effectiveness of this algorithm are examined using a set of benchmark instances and compared with existing algorithms. The results show that the proposed algorithm could obtain competitive results within reasonable computing times.
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Jia-WeiChang and 張家瑋. "A Semantic Similarity Evaluation Algorithm for English Short-Texts." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/19015816367253207242.

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碩士
國立成功大學
工程科學系碩博士班
100
In recent years, there is a growing need for precise and fast Information Retrieval (IR) services, which gradually push information providing systems to use Information Retrieval techniques based on natural language queries. This study presents an algorithm to evaluate the semantic similarity between English short texts and aims to enhance the execution efficiency and the accuracy on information retrieving. For the embedded information in a short text is limited, applying well-known IR models, such as LSA, HAL and etc., directly may not always perfectly quantified the semantic of the short text. This study tries to take the advantage of syntactical relationships derived by natural language techniques and proposes a algorithm for quantifying words in a short text by using word sense disambiguation and semantic similarity measures by WordNet. The proposed algorithm proves to be comparable to the now best performing aldorithms, and has a Pearson Correlation of 0.9111 and an accuracy of 71.59%, in the small scale and the large scale datasets, respectively. This study uses syntactic information from short texts to clear the ambiguitits of roles of words to improve the semantic similarity mesure of the short texts. The experimental results confirm that the algorithm has fair performance and good efficiency and could be useful for various practical applications in Information Retrieval and Natural Language Processing.
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Lin, Hsiao-Jou, and 林孝柔. "Flexible Job Shop Scheduling using a Multiobjective Memetic Algorithm." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/51223601763201114988.

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Chung, Chi-Hsun, and 鍾奇勳. "Solving Job-Shop Scheduling Problems by Boltzmann Genetic Algorithm." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/63294904306332949902.

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Abstract:
碩士
國立臺灣科技大學
工業管理系
97
Job-shop scheduling problem (JSP), which was wildly used in industries, plays a vital role in manufacture scheduling. Many of the high-tech industries such as semiconductor industries, TFT-LCD industries belong to the Job-shop scheduling. Nevertheless, due to the variation of JSP, its combinatorial optimization problem in scheduling is recognized as one of the most complicated NP-hard problems. Many experts and scholars use the Generic algorithm to seek out the JSP problem, and its powerful searching ability of Genetic algorithm (GA) was widely applied in scheduling problem. However, the insufficiency of searching partial area in GA makes the process of evolutionary searching easily fall into the local optimal solution, lowering the efficiency of seeking out the optimal solution. Based on this phenomenon, this study combines GA with Boltzmann function in Simulated Annealing algorithm, which is characterized as not easily fall into local optimal solution, developing Boltzmann Genetic Algorithm (BGA), and aims to compare the quality and efficiency between BGA and traditional GA in minimum makespan in JSP. The result of this study indicates the advantageous of BGA over traditional GA in seeking out JSP, suggesting that the BGA can save extra time and cost, and benefit industries in planning manufacturing scheduling.
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