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Dissertations / Theses on the topic 'Genetic Particle Swarm Optimization'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Morcos, Karim M. "Genetic network parameter estimation using single and multi-objective particle swarm optimization." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/9207.

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Master of Science<br>Department of Electrical and Computer Engineering<br>Sanjoy Das<br>Stephen M. Welch<br>Multi-objective optimization problems deal with finding a set of candidate optimal solutions to be presented to the decision maker. In industry, this could be the problem of finding alternative car designs given the usually conflicting objectives of performance, safety, environmental friendliness, ease of maintenance, price among others. Despite the significance of this problem, most of the non-evolutionary algorithms which are widely used cannot find a set of diverse and nearly optima

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2

Muthuswamy, Shanthi. "Discrete particle swarm optimization algorithms for orienteering and team orienteering problems." Diss., Online access via UMI:, 2009.

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3

Franz, Wayne. "Multi-population PSO-GA hybrid techniques: integration, topologies, and parallel composition." Springer, 2013. http://hdl.handle.net/1993/23842.

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Recent work in metaheuristic algorithms has shown that solution quality may be improved by composing algorithms with orthogonal characteristics. In this thesis, I study multi-population particle swarm optimization (MPSO) and genetic algorithm (GA) hybrid strategies. I begin by investigating the behaviour of MPSO with crossover, mutation, swapping, and all three, and show that the latter is able to solve the most difficult benchmark functions. Because GAs converge slowly and MPSO provides a large degree of parallelism, I also develop several parallel hybrid algorithms. A composite approach exec

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4

Sheehan, Shane P. "Spacecraft Trajectory Optimization Suite (STOPS): Optimization of Low-Thrust Interplanetary Spacecraft Trajectories Using Modern Optimization Techniques." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1901.

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The work presented here is a continuation of Spacecraft Trajectory Optimization Suite (STOpS), a master’s thesis written by Timothy Fitzgerald at California Polytechnic State University, San Luis Obispo. Low-thrust spacecraft engines are becoming much more common due to their high efficiency, especially for interplanetary trajectories. The version of STOpS presented here optimizes low-thrust trajectories using the Island Model Paradigm with three stochastic evolutionary algorithms: the genetic algorithm, differential evolution, and particle swarm optimization. While the algorithms used here we

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Espinosa, Edgard. "Design Optimization of Submerged Jet Nozzles for Enhanced Mixing." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/501.

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The purpose of this thesis was to identify the optimal design parameters for a jet nozzle which obtains a local maximum shear stress while maximizing the average shear stress on the floor of a fluid filled system. This research examined how geometric parameters of a jet nozzle, such as the nozzle's angle, height, and orifice, influence the shear stress created on the bottom surface of a tank. Simulations were run using a Computational Fluid Dynamics (CFD) software package to determine shear stress values for a parameterized geometric domain including the jet nozzle. A response surface was crea

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Grobler, Jacomine. "Particle swarm optimization and differential evolution for multi-objective multiple machine scheduling." Diss., Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-05062009-164124/.

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7

Hadavi, Hamid. "Isometry Registration Among Deformable Objects, A Quantum Optimization with Genetic Operator." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/24286.

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Non-rigid shapes are generally known as objects whose three dimensional geometry may deform by internal and/or external forces. Deformable shapes are all around us, ranging from protein molecules, to natural objects such as the trees in the forest or the fruits in our gardens, and even human bodies. Two deformable shapes may be related by isometry, which means their intrinsic geometries are preserved, even though their extrinsic geometries are dissimilar. An important problem in the analysis of the deformable shapes is to identify the three-dimensional correspondence between two isometric shap

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Zuniga, Virgilio. "Bio-inspired optimization algorithms for smart antennas." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5766.

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This thesis studies the effectiveness of bio-inspired optimization algorithms in controlling adaptive antenna arrays. Smart antennas are able to automatically extract the desired signal from interferer signals and external noise. The angular pattern depends on the number of antenna elements, their geometrical arrangement, and their relative amplitude and phases. In the present work different antenna geometries are tested and compared when their array weights are optimized by different techniques. First, the Genetic Algorithm and Particle Swarm Optimization algorithms are used to find the best

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Al-Obaidi, Mohanad. "ENAMS : energy optimization algorithm for mobile wireless sensor networks using evolutionary computation and swarm intelligence." Thesis, De Montfort University, 2010. http://hdl.handle.net/2086/5187.

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Although traditionally Wireless Sensor Network (WSNs) have been regarded as static sensor arrays used mainly for environmental monitoring, recently, its applications have undergone a paradigm shift from static to more dynamic environments, where nodes are attached to moving objects, people or animals. Applications that use WSNs in motion are broad, ranging from transport and logistics to animal monitoring, health care and military. These application domains have a number of characteristics that challenge the algorithmic design of WSNs. Firstly, mobility has a negative effect on the quality of

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10

Liu, Fang. "Nature inspired computational intelligence for financial contagion modelling." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/8208.

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Financial contagion refers to a scenario in which small shocks, which initially affect only a few financial institutions or a particular region of the economy, spread to the rest of the financial sector and other countries whose economies were previously healthy. This resembles the “transmission” of a medical disease. Financial contagion happens both at domestic level and international level. At domestic level, usually the failure of a domestic bank or financial intermediary triggers transmission by defaulting on inter-bank liabilities, selling assets in a fire sale, and undermining confidence

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Ural, Mustafa. "Solution Of The Antenna Placement Problem By Means Of Global Optimization Techniques." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612674/index.pdf.

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In this thesis work, minimization of platform-based coupling between the antennas of two VHF radios on an aircraft platform and two HF radios on a ship platform is aimed. For this purpose<br>an optimal antenna placement, which yields minimum average coupling between the antennas over the whole frequency band of operation is determined for each platform. Two important global optimization techniques, namely Genetic Algorithm Optimization and Particle Swarm Optimization, are used in determination of these optimal antenna placements. Aircraft &amp<br>ship platforms and antennas placed on them are

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12

Raj, Ashish. "Evolutionary Optimization Algorithms for Nonlinear Systems." DigitalCommons@USU, 2013. http://digitalcommons.usu.edu/etd/1520.

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Many real world problems in science and engineering can be treated as optimization problems with multiple objectives or criteria. The demand for fast and robust stochastic algorithms to cater to the optimization needs is very high. When the cost function for the problem is nonlinear and non-differentiable, direct search approaches are the methods of choice. Many such approaches use the greedy criterion, which is based on accepting the new parameter vector only if it reduces the value of the cost function. This could result in fast convergence, but also in misconvergence where it could lead the

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Pillai, Ajit Chitharanjan. "On the optimization of offshore wind farm layouts." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25470.

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Layout optimization of offshore wind farms seeks to automate the design of the wind farm and the placement of wind turbines such that the proposed wind farm maximizes its potential. The optimization of an offshore wind farm layout therefore seeks to minimize the costs of the wind farm while maximizing the energy extraction while considering the effects of wakes on the resource; the electrical infrastructure required to collect the energy generated; the cost variation across the site; and all technical and consenting constraints that the wind farm developer must adhere to. As wakes, electrical

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14

Ras, Marthinus Nicolaas. "The development of some rotationally invariant population based optimization methods." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80172.

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Thesis (MScEng)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: In this study we consider the lack of rotational invariance of three different population based optimization methods, namely the particle swarm optimization (PSO) algorithm, the differential evolution (DE) algorithm and the continuous-parameter genetic algorithm (CPGA). We then propose rotationally invariant versions of these algorithms. We start with the PSO. The so-called classical PSO algorithmis known to be variant under rotation, whereas the linear PSO is rotationally invariant. This invariance however, comes at the

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RUEDA, CAMILO VELASCO. "ESNPREDICTOR: TIME SERIES FORECASTING APPLICATION BASED ON ECHO STATE NETWORKS OPTIMIZED BY GENETICS ALGORITHMS AND PARTICLE SWARM OPTIMIZATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24785@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>A previsão de séries temporais é fundamental na tomada de decisões de curto, médio e longo prazo, em diversas áreas como o setor elétrico, a bolsa de valores, a meteorologia, entre outros. Tem-se na atualidade uma diversidade de técnicas e modelos para realizar essas previsões, mas as ferramentas estatísticas são as mais utilizadas principalmente por apresentarem um maior grau d

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Ibrahem, Al-mehdi Mohamed M. "Scheduling optimization of cellular flowshop with sequence dependent setup times." Proceedings of the 47th CIRP Conference on Manufacturing Systems, 2014. http://hdl.handle.net/1993/30730.

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In cellular manufacturing systems, minimization of the completion time has a great impact on the production time, material flow, and productivity. An effective scheduling is crucial to attaining the advantages of cellular manufacturing systems. This dissertation attempts to solve the Flowshop Manufacturing Cell (cellular flowshop) Scheduling Problem with Sequence Dependent Setup Times (FMCSP with SDSTs) considering two performance measures: the total flow time as a mono objective, and the makespan and total flow time combined as a bi-criteria scheduling problem. The proposed problem is kno

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Sheikhi, Mehrabadi Elham. "Multi-Objective Optimization of Combined Heat and Power Industrial Microgrid." Thesis, The University of Sydney, 2020. https://hdl.handle.net/2123/21868.

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With the advent of distributed energy resources (DERs), such as solar photovoltaic (PV), distributed storages (DSs), and combined heat and power (CHP) generators, an opportunity was given to various customers to be satisfied with their local electricity and heat providers. Microgrid is a small-scale, localized power network that encompasses DERs, loads, and controllers. Microgrids could be a promising alternative for the conventional power system to solve environmental and economic concerns. Recently, CHP-based microgrids have widely attracted attention due to the cost effectiveness and poll

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Mullen, Patrick Bowen. "Learning in Short-Time Horizons with Measurable Costs." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/808.

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Dynamic pricing is a difficult problem for machine learning. The environment is noisy, dynamic and has a measurable cost associated with exploration that necessitates that learning be done in short-time horizons. These short-time horizons force the learning algorithms to make pricing decisions based on scarce data. In this work, various machine learning algorithms are compared in the context of dynamic pricing. These algorithms include the Kalman filter, artificial neural networks, particle swarm optimization and genetic algorithms. The majority of these algorithms have been modified to handle

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Srnec, Pavel. "Optimalizace nastavení závodního vozu simulátoru TORCS." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236557.

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This master's thesis is about nature optimalization technigues. Evolution algortihms together with main thesis topic, Particle Swarm Optimization, is introduced in the following chapter. Car setup and simulator TORCS are introduced in next chapter. Design and implementation are introduced in next chapters. Destination of t master's thesis is finding optimal car setups for different curcuits.

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Wei, Xing. "Optimization of Strongly Nonlinear Dynamical Systems Using a Modified Genetic Algorithm With Micro-Movement (MGAM)." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/450.

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The genetic algorithm (GA) is a popular random search and optimization method inspired by the concepts of crossover, random mutation, and natural selection from evolutionary biology. The real-valued genetic algorithm (RGA) is an improved version of the genetic algorithm designed for direct operation on real-valued variables. In this work, a modified version of a genetic algorithm is introduced, which is called a modified genetic algorithm with micro-movement (MGAM). It implements a particle swarm optimization(PSO)-inspired micro-movement phase that helps to improve the convergence rate, while

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21

Abdussalam, Fathi M. A. "Antenna design using optimization techniques over various computaional electromagnetics. Antenna design structures using genetic algorithm, Particle Swarm and Firefly algorithms optimization methods applied on several electromagnetics numerical solutions and applications including antenna measurements and comparisons." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17217.

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Dealing with the electromagnetic issue might bring a sort of discontinuous and nondifferentiable regions. Thus, it is of great interest to implement an appropriate optimisation approach, which can preserve the computational resources and come up with a global optimum. While not being trapped in local optima, as well as the feasibility to overcome some other matters such as nonlinear and phenomena of discontinuous with a large number of variables. Problems such as lengthy computation time, constraints put forward for antenna requirements and demand for large computer memory, are very com

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Babatunde, Oluleye Hezekiah. "A neuro-genetic hybrid approach to automatic identification of plant leaves." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1733.

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Plants are essential for the existence of most living things on this planet. Plants are used for providing food, shelter, and medicine. The ability to identify plants is very important for several applications, including conservation of endangered plant species, rehabilitation of lands after mining activities and differentiating crop plants from weeds. In recent times, many researchers have made attempts to develop automated plant species recognition systems. However, the current computer-based plants recognition systems have limitations as some plants are naturally complex, thus it is difficu

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23

Izquierdo, Rafael Crespo. "Planejamento de trajetórias livres de colisão : um estudo considerando restrições cinemáticas e dinâmicas de um manipulador pneumático por meio de algoritmos metaheurísticos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/172762.

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presente trabalho consolida um estudo para o planejamento de trajetória livre de colisão para um robô pneumático com 5 graus de liberdade aplicando três algoritmos metaheurísticos: algoritmos metaheurísticos por vagalumes, algoritmos metaheurísticos por enxames de partículas e algoritmos genéticos. No que se refere à aplicação de algoritmos metaheurísticos ao estudo de planejamento de trajetória de robôs manipuladores na presença de obstáculos, existem diferentes tipos de técnicas para evitar colisões que consideram os efeitos cinemáticos e dinâmicos na obtenção de trajetórias com o menor temp

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KUMAR, NEERAJ. "DESIGNING OF MARKET MODEL, EFFECTIVE PRICE FORECASTING TOOL AND BIDDING STRATEGY FOR INDIAN ELECTRICITY MARKET." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18910.

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The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. Penetration of renewable energy resources into grid is necessary to meet the elevated demand of electricity. In view of this penetration of solar and wind power growing enormously across the globe. Solar energy is widely escalating in terms of generation and capacity addition due its better predictability over wind energy. Electricity pricing is one of the important aspects for power system planning and it felicitates information for the electricity b

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NOBILE, MARCO SALVATORE. "Evolutionary Inference of Biological Systems Accelerated on Graphics Processing Units." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/75434.

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In silico analysis of biological systems represents a valuable alternative and complementary approach to experimental research. Computational methodologies, indeed, allow to mimic some conditions of cellular processes that might be difficult to dissect by exploiting traditional laboratory techniques, therefore potentially achieving a thorough comprehension of the molecular mechanisms that rule the functioning of cells and organisms. In spite of the benefits that it can bring about in biology, the computational approach still has two main limitations: first, there is often a lack of adequate kn

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Kesler, René. "Optimalizace metaheuristikami v Pythonu pomocí knihovny DEAP." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-401489.

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{This thesis deals with optimization by means of metaheuristics, which are used for complicated engineering problems that cannot be solved by classical methods of mathematical programming. At the beginning, choosed metaheuristics are described: simulated annealing, particle swarm optimization and genetic algorithm; and then they are compared with use of test functions. These algorithms are implemented in Python programming language with use of package called DEAP, which is also described in this thesis. Algorithms are then applied for optimization of design parameters of the heat storage unit.

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MIRANDA, Pericles Barbosa Cunha de. "Uma hiper-heurística híbrida para a otimização de algorítmos." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/18703.

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Submitted by Rafael Santana (rafael.silvasantana@ufpe.br) on 2017-05-04T18:13:43Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Teste - Péricles Miranda.pdf: 1959669 bytes, checksum: 8b0b1e3f94dd3295bce6153865564a12 (MD5)<br>Made available in DSpace on 2017-05-04T18:13:43Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Teste - Péricles Miranda.pdf: 1959669 bytes, checksum: 8b0b1e3f94dd3295bce6153865564a12 (MD5) Previous issue date: 2016-08-22<br>A escolha de algoritmos ou heurísticas

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Haji, Agha Mohammad Zarbaf Seyed Ehsan. "Vibration-based Cable Tension Estimation in Cable-Stayed Bridges." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535636861655531.

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Mucs, Daniel. "Computational methods for prediction of protein-ligand interactions." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/computational-methods-for-prediction-of-proteinligand-interactions(33ad0b24-ef7b-4dff-8e28-597a2f34e079).html.

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This thesis contains three main sections. In the first section, we examine methodologies to discriminate Type II protein kinase inhibitors from the Type I inhibitors. We have studied the structure of 55 Type II kinase inhibitors and have notice specific descriptive geometric features. Using this information we have developed a pharmacophore and a shape based screening approach. We have found that these methods did not effectively discriminate between the two inhibitor types used independently, but when combined in a consecutive way – pharmacophore search first, then shape based screening, we h

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Kingry, Nathaniel. "Heuristic Optimization and Sensing Techniques for Mission Planning of Solar-Powered Unmanned Ground Vehicles." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523874767812408.

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Hanek, Petr. "Implementace problému směrování vozidel pomocí algoritmu mravenčích kolonií a částicových rojů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400931.

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This diploma thesis focuses on meta-heuristic algorithms and their ability to solve difficult optimization problems in polynomial time. The thesis describes different kinds of meta-heuristic algorithms such as genetic algorithm, particle swarm optimization or ant colony optimization. The implemented application was written in Java and contains ant colony optimization for capacitated vehicle routing problem and particle swarm optimization which finds the best possible parameters for ant colonies.

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Cai, Xinye. "A multi-objective GP-PSO hybrid algorithm for gene regulatory network modeling." Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1492.

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Kubalová, Eva. "Využití evolučních algoritmů pro lícování obrazu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316844.

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The diploma thesis deals with the image registration using evolutionary algorithms from metaheuristic optimization techniques which are considered recent and widely used. The frst part of the thesis contains theoretical description of components in image registration and later focuses on the ultrasound images. In that part, the thesis explains chosen evolutionary algorithms. Three optimization methods have been implemented, in particular genetic algorithm, particle swarm optimization and frey algorithm. Chosen similarity metrics for optimization are sum of squared dierences, cosine similarity

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Devarakonda, SaiPrasanth. "Particle Swarm Optimization." University of Dayton / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1335827032.

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

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Master thesis is focused on optimization of cogeneration system for purpose of rating optimization methods and evaluating properties of these methods. For each method there is description together with block schemes. First part of thesis is devoted to description of methods and their comparison. Second part consists of development of hybrid algorithm, which is used to optimize cogeneration systém model. Each algorithm compared is together with hybrid algorithms included in annexes.

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Hinkle, Kurt Berlin. "An Automated Method for Optimizing Compressor Blade Tuning." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6230.

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Because blades in jet engine compressors are subject to dynamic loads based on the engine's speed, it is essential that the blades are properly "tuned" to avoid resonance at those frequencies to ensure safe operation of the engine. The tuning process can be time consuming for designers because there are many parameters controlling the geometry of the blade and, therefore, its resonance frequencies. Humans cannot easily optimize design spaces consisting of multiple variables, but optimization algorithms can effectively optimize a design space with any number of design variables. Automated blade

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RIBEIRO, Reiga Ramalho. "Reconstrução de imagens de tomografia por impedância elétrica usando evolução diferencial." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/17899.

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Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-09-20T13:03:02Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Versão_Digital_REIGA.pdf: 3705889 bytes, checksum: 551e1d47969ce5d1aa92cdb311f41304 (MD5)<br>Made available in DSpace on 2016-09-20T13:03:02Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Versão_Digital_REIGA.pdf: 3705889 bytes, checksum: 551e1d47969ce5d1aa92cdb311f41304 (MD5) Previous issue date: 2016-02-23<br>CAPES<br>A Tomogr

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Al-kazemi, Buthainah Sabeeh No'man. "Multiphase particle swarm optimization." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

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Ференс, Дмитро Андрійович. "Дослідження методів розподілу ресурсів критичної ІТ інфраструктури за допомогою технологій штучного інтелекту". Master's thesis, Київ, 2018. https://ela.kpi.ua/handle/123456789/23028.

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Проведено аналіз існуючих проблем в управлінні ресурсами ІТ інфраструктури. Запропоновані способи застосування технологій штучного інтелекту для вирішення задачі розподілу ресурсів. Запропоновано модифікований варіант фітнес-функції, що дозволяє здійснювати оптимальний розподіл елементів інфраструктури, враховуючи їх поточне розміщення. Проведено порівняння розроблених алгоритмів з існуючими та підтвердженно високу якість отриманих результатів.<br>The analysis of existing problems in IT infrastructure resources management is carried out. Methods of application of artificial intelligence techno

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Götthans, Tomáš. "Pokročilé algoritmy analýzy datových sekvencí v Matlabu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218618.

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Cílem této práce je se seznámení s možnostmi programu Matlab z hlediska detailní analýzy deterministických dynamických systémů. Jedná se především o analýzu časové posloupnosti a o nalezení Lyapunových exponentů. Dalším cílem je navrhnout algoritmus umožňující specifikovat chování systému na základě znalosti příslušných diferenciálních rovnic. To znamená, nalezení chaotických systémů.

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Besbes, Mariem. "Modélisation et résolution du problème d’implantation des ateliers de production : proposition d’une approche combinée Algorithme Génétique – Algorithme A*." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC094.

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Pour faire face à la concurrence, les entreprises cherchent à améliorer leurs performances industrielles. L’une des solutions à ce défi réside dans la détermination de la meilleure configuration des ateliers de production. Ce type de problème est connu en anglais par Facility Layout Problem « FLP». Dans ce contexte, notre travail propose une méthodologie pour la définition de la configuration d’atelier à travers une approche réaliste. Plus précisément, notre objectif est de prendre en compte les distances réelles parcourues par les pièces dans l’atelier et des contraintes liées au système qui

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Scheepers, Christiaan. "Multi-guided particle swarm optimization : a multi-objective particle swarm optimizer." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/64041.

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An exploratory analysis in low-dimensional objective space of the vector evaluated particle swarm optimization (VEPSO) algorithm is presented. A novel visualization technique is presented and applied to perform the exploratory analysis. The exploratory analysis together with a quantitative analysis revealed that the VEPSO algorithm continues to explore without exploiting the well-performing areas of the search space. A detailed investigation into the influence that the choice of archive implementation has on the performance of the VEPSO algorithm is presented. Both the Pareto-optimal front (PO

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Djaneye-Boundjou, Ouboti Seydou Eyanaa. "Particle Swarm Optimization Stability Analysis." University of Dayton / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1386413941.

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Hong, Ci-Wei, and 洪齊尉. "Integration of Genetic Algorithm and Particle Swarm Optimization Algorithm for Portfolio Optimization." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/nhvj26.

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碩士<br>國立臺北科技大學<br>工業工程與管理研究所<br>97<br>In the investment market, investors concern greatly about investment target selection and asset allocation under the risk of investment market. Therefore, this research applies soft computing methods to develop a two-stage portfolio method. The first stage utilize a Data Envelopment Analysis (DEA) - CCR model to develop a model of funds selection, with the second stage integrates Genetic Algorithm (GA) and Particle Swarm Optimization Algorithm (PSO) to develop two method, GPSO1 and GPSO2, for assets allocation. The experiments were conducted by using the T

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Huang, Chien-Chang, and 黃建彰. "Genetic Algorithm with Particle Swarm Optimization for Multiple Sequence Alignment." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/88695419642629138038.

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碩士<br>義守大學<br>工業工程與管理學系碩士班<br>96<br>After the completion of human genome sequencing, 2.9 billion letters of DNA code have been read. The finished human genome sequence records the mechanism of inherited traits. If exploring and analyzing these substantial genomic data effectively, we can identify genes involved in more complex diseases and power drug discovery research. However, only a few of sequences are meaningful in the genomic data. The DNA sequences of organisms must be aligned so that we can find out the implicit biological information. The main tool of analyzing DNA sequences is sequen

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(5931074), Md Saiful Islam. "Dynamic Electronic Asset Allocation Comparing Genetic Algorithm with Particle Swarm Optimization." Thesis, 2019.

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<div>The contribution of this research work can be divided into two main tasks: 1) implementing this Electronic Warfare Asset Allocation Problem (EWAAP) with the Genetic Algorithm (GA); 2) Comparing performance of Genetic Algorithm to Particle Swarm Optimization (PSO) algorithm. This research problem implemented Genetic Algorithm in C++ and used QT Data Visualization for displaying three-dimensional space, pheromone, and Terrain. The Genetic algorithm implementation maintained and preserved the coding style, data structure, and visualization from the PSO implementation. Although the Genetic Al

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Islam, Md Saiful. "Dynamic electronic asset allocation comparing genetic algorithm with particle swarm optimization." Thesis, 2018. http://hdl.handle.net/1805/17916.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>The contribution of this research work can be divided into two main tasks: 1) implementing this Electronic Warfare Asset Allocation Problem (EWAAP) with the Genetic Algorithm (GA); 2) Comparing performance of Genetic Algorithm to Particle Swarm Optimization (PSO) algorithm. This research problem implemented Genetic Algorithm in C++ and used QT Data Visualization for displaying three-dimensional space, pheromone, and Terrain. The Genetic algorithm implementation maintained and preserved the coding style, data structure, and visualizat

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Lin, Lu-Mei, and 林如梅. "Integration of Genetic Algorithm and Particle Swarm Optimization for Clustering Analysis." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/zt8hpr.

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碩士<br>國立臺北科技大學<br>工業工程與管理研究所<br>96<br>This study intends to propose a novel clustering analysis technique, Hybrid particle swarm optimization algorithm (Hybrid PSO), which integrates the particle swarm optimization algorithm, genetic algorithm and K-means method together. In order to evaluate its computational performance, some clustering analysis methods including genetic algorithm (GA), genetic K-means algorithm (GKA), PSO clustering, particle swarm K-means optimization (PSKO), genetic algorithm- particle swarm optimization (GA-PSO) and genetic algorithm- particle swarm K-means optimization

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Syu, Yi-Jhen, and 徐儀蓁. "Integration of Particle Swarm Optimization and Genetic Algorithm for Dynamic Clustering." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/3e8ny8.

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碩士<br>國立臺北科技大學<br>工業工程與管理研究所<br>97<br>With the advancement of technology, the methods of clustering analysis are continually proposed. Even though, most of the clustering methods still need to set the number of cluters. This study intends to propose a novel dynamic clustering technique - Dynamic Clustering using Particle Swarm Optimization and Genetic Algorithm (DCPG), which does not need to set the number of cluters in advance. By the features of data, the method could auomatically cluster together into a suitable cluster number. This study employees four benchmark datasets, Iris, Wine, Glas

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Chen, Hsin-Tsun, and 陳信村. "The Research of New Particle Swarm Optimization Method Based on Genetic Algorithm." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/73560671933331264939.

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碩士<br>國立高雄海洋科技大學<br>輪機工程研究所<br>98<br>In this study, a new intelligent optimization algorithm, namely, embedded particle swarm optimization (PSO) with genetic algorithm (GA) is investigated. The basic motivations of proposed algorithm is combine real number continuous genetic algorithm with distribution, selection, mutation, and linearly decreasing weight method into particle swarm optimization algorithm. It is more effective on fast computing and avoids the local minimum problem. The proposed algorithm, compare to the traditional particle swarm optimization and genetic algorithm, is exam by fo

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