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Dissertations / Theses on the topic 'Population-based algorithm'

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1

Nilsson, Mikael. "Parameter Tuning Experiments of Population-based Algorithms." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-13836.

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In this study, three different algorithms are implemented to solve thecapacitated vehicle routing problem with and without time windows:ant colony optimization, a genetic algorithm and a genetic algorithmwith self-organizing map. For the capacitated vehicle routing problemthe Augerat et al’s benchmark problems were used and for the capaci-tated vehicle routing problem with time windows the Solomon’sbenchmark problems. All three algorithms were tuned over thirtyinstances per problem with the tuners SPOT and ParamILS. The tuningresults from all instances were combined to the final parameter valu
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Vuckovich, David N. "An open-source population indifference zone-based algorithm for simulation optimization." Connect to resource, 2009. http://hdl.handle.net/1811/36949.

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Liao, Tianjun. "Population-based heuristic algorithms for continuous and mixed discrete-continuous optimization problems." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209439.

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Continuous optimization problems are optimization problems where all variables<p>have a domain that typically is a subset of the real numbers; mixed discrete-continuous<p>optimization problems have additionally other types of variables, so<p>that some variables are continuous and others are on an ordinal or categorical<p>scale. Continuous and mixed discrete-continuous problems have a wide range<p>of applications in disciplines such as computer science, mechanical or electrical<p>engineering, economics and bioinformatics. These problems are also often hard to<p>solve due to their inherent diffi
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Siqueira, Gomes Hugo. "Meta learning for population-based algorithms in black-box optimization." Master's thesis, Université Laval, 2021. http://hdl.handle.net/20.500.11794/68764.

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Les problèmes d’optimisation apparaissent dans presque tous les domaines scientifiques. Cependant, le processus laborieux de conception d’un optimiseur approprié peut demeurer infructueux. La question la plus ambitieuse de l’optimisation est peut-être de savoir comment concevoir des optimiseurs suffisamment flexibles pour s’adapter à un grand nombre de scénarios, tout en atteignant des performances de pointe. Dans ce travail, nous visons donner une réponse potentielle à cette question en étudiant comment faire un méta-apprentissage d’optimiseurs à base de population. Nous motivons et décrivons
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al-Rifaie, Mohammad Majid. "Information sharing impact of stochastic diffusion search on population-based algorithms." Thesis, Goldsmiths College (University of London), 2011. http://research.gold.ac.uk/6708/.

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This work introduces a generalised hybridisation strategy which utilises the information sharing mechanism deployed in Stochastic Diffusion Search when applied to a number of population-based algorithms, effectively merging this nature-inspired algorithm with some population-based algorithms. The results reported herein demonstrate that the hybrid algorithm, exploiting information-sharing within the population, improves the optimisation capability of some well-known optimising algorithms, including Particle Swarm Optimisation, Differential Evolution algorithm and Genetic Algorithm. This hybrid
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6

Hajizadeh, Yasin. "Population-based algorithms for improved history matching and uncertainty quantification of petroleum reservoirs." Thesis, Heriot-Watt University, 2011. http://hdl.handle.net/10399/2423.

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In modern field management practices, there are two important steps that shed light on a multimillion dollar investment. The first step is history matching where the simulation model is calibrated to reproduce the historical observations from the field. In this inverse problem, different geological and petrophysical properties may provide equally good history matches. Such diverse models are likely to show different production behaviors in future. This ties the history matching with the second step, uncertainty quantification of predictions. Multiple history matched models are essential for a
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7

Montero, Elisabeth. "Calibration strategies for bio-inspired population-based algorithms that solve combinatorial optimization problems." Nice, 2011. http://www.theses.fr/2011NICE4040.

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La sélection de valeurs adéquates pour les paramètres des algorithmes bio-inspirés est un processus crucial pour obtenir de bonnes performances. C’est un processus complexe étant donné que les valeurs des paramètres dépendent en général du problème que l’on cherche à résoudre. Il est de plus très coûteux en temps, et les paramètres ne sont pas complètement indépendants entre eux. La première contribution de cette thèse consiste en une étude comparative des caractéristiques et performances des différentes méthodes connues dans la littérature pour ajuster les paramètres, en analysant leurs avant
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8

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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Khouadjia, Mostepha Redouane. "Solving dynamic vehicle routing problems : from single-solution based metaheuristics to parallel population based metaheuristics." Thesis, Lille 1, 2011. http://www.theses.fr/2011LIL10140/document.

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Beaucoup de problèmes dans le monde réel ont une nature dynamique et peuvent être modélisés comme des problèmes dynamiques d'optimisation combinatoire. Cependant, les travaux de recherches sur l'optimisation dynamique se concentrent essentiellement sur les problèmes d'optimisation continue et ils ciblent rarement les problèmes combinatoires. Une des applications dans le domaine des problèmes dynamiques combinatoires ayant reçu un intérêt croissant au cours de ces dernières décennies est le système de transport en ligne où dynamique. Un problème typique de ce domaine est le Problème Dynamique d
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10

Riahi, Vahid. "Constraint Directed Scheduling." Thesis, Griffith University, 2019. http://hdl.handle.net/10072/386545.

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Scheduling is a decision-making process, which is employed to allocate resources to tasks in a given time. Scheduling problems are in general NP-hard. In order to solve scheduling problems, three common types of methods have been used: exact methods (e.g., branch & bound and dynamic programming), population based metaheuristics (e.g., genetic algorithm and ant colony optimisation), and local search (LS) algorithms (e.g., simulated annealing and iterated local search). Exact methods are not able to address the practical-sized problems effectively with regard to both CPU times and solution quali
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Vong, Camille. "Model-Based Optimization of Clinical Trial Designs." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-233445.

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General attrition rates in drug development pipeline have been recognized as a necessity to shift gears towards new methodologies that allow earlier and correct decisions, and the optimal use of all information accrued throughout the process. The quantitative science of pharmacometrics using pharmacokinetic-pharmacodynamic models was identified as one of the strategies core to this renaissance. Coupled with Optimal Design (OD), they constitute together an attractive toolkit to usher more rapidly and successfully new agents to marketing approval. The general aim of this thesis was to investigat
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Silva, Marcelo Ribeiro da. "Otimiza??o de superf?cies seletivas de frequ?ncia com elementos pr?-fractais utilizando rede neural MLP e algoritmos de busca populacional." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15242.

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Made available in DSpace on 2014-12-17T14:55:18Z (GMT). No. of bitstreams: 1 MarceloRS_TESE.pdf: 2113878 bytes, checksum: 1cc62a66f14cc48f2e97f986a4dbbb8d (MD5) Previous issue date: 2014-01-27<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applica
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13

Hsu, Wei-Hsiang, and 徐偉翔. "A Population-Based Evolutionary Algorithm Based on Yin-Yang Harmony for Global Optimization Problems." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/2d96u8.

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碩士<br>國立臺灣海洋大學<br>系統工程暨造船學系<br>102<br>In this research, a population-based evolutionary algorithm is developed for global optimization problems including several benchmark problems and engineering optimizations. The algorithm is established based on the frame of the particle swarm optimization(PSO), in which four search strategies are adopted, such as the orthogonal arrays(OA) for creating the initial population, the principal component analysis(PCA) for changing the design variables, the stretching technique(ST) for changing the objective function, the cooperative grid method(CGM) for generat
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14

Pampara, Gary. "Angle modulated population based algorithms to solve binary problems." Diss., 2012. http://hdl.handle.net/2263/22801.

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Recently, continuous-valued optimization problems have received a great amount of focus, resulting in optimization algorithms which are very efficient within the continuous-valued space. Many optimization problems are, however, defined within the binary-valued problem space. These continuous-valued optimization algorithms can not operate directly on a binary-valued problem representation, without algorithm adaptations because the mathematics used within these algorithms generally fails within a binary problem space. Unfortunately, such adaptations may alter the behavior of the algorithm, poten
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Huang, Wei-che, and 黃偉哲. "Particle Swarm Optimization Algorithm Applied to Base Station Construction Based on Population Density." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/85023376171752733233.

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碩士<br>國立中央大學<br>通訊工程學系在職專班<br>101<br>Mobile communication has great progress in just a few years. People can access the internet by mobile; and the speed of internet can support high-definition video. Therefore, the user of mobile communication have Increased significantly. Surge of users, it will cause network congestion in areas of high population density, and then the connection is not easy. When the location of base station disposes at bad locations, the signal coverage is poor. Or an excessive number of base station constructions will result in increases in operating costs. This thesis wi
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16

Lin, Yi-Sz. "Development of Algorithms to Estimate Post-Disaster Population Dislocation--A Research-Based Approach." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-3266.

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This study uses an empirical approach to develop algorithms to estimate population dislocation following a natural disaster. It starts with an empirical reexamination of the South Dade Population Impact Survey data, integrated with the Miami-Dade County tax appraisal data and 1990 block group census data, to investigate the effects of household and neighborhood socioeconomic characteristics on household dislocation. The empirical analyses found evidence suggesting that households with higher socio-economic status have a greater tendency to leave their homes following a natural disaster. Then o
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Tseng, I.-Hsiang, and 曾奕翔. "Global Non-Dominated Solution based Sub-Population Genetic Algorithm for Multi-Objective Production Scheduling Problems." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/15993166844386325320.

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碩士<br>開南大學<br>資訊管理學系<br>99<br>Whatever industry, from traditional manufacturers to factories controlled automatically, machinery makes flows faster and more sophicated. During the process, however, problems cannot be avoided; as a consequence, more efficient working order is necessary in order to attain profits. That is why scheduling has been placing great value on. The researcher adapted SPGA for GND-SPGA, and also used GNDS to analyze the best characteristics, applying to Elitist Strategy for the purpose of attaining the rapidest results and possible scheduling effects. The study aimed to i
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18

Chu, Shen-Way, and 朱顯偉. "Population Pharmacokinetics of Aminoglycoside Antibiotics in Chinese -- studies based on nonparametric expectation maximization algorithm (NPEM) and neural network." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/90262373386652005999.

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碩士<br>國立臺灣大學<br>藥學研究所<br>84<br>Aminoglycoside antibiotics are agents with narrow therapeutic range. Therapeutic drug monitoring is often required to ensure their effectiveness and safety in clinical use. However, the pharmacokinetics used to estimate the dosage regimen of aminoglycoside antibiotics to date all originated from abroad. Based on the data collected from routine monitoring of the plasma concentrations of the four aminoglycoside antibiotics (amikacin, gentamicin, netilmicin, tobr
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19

CHIU, SHAO-WEN, and 邱紹文. "Assessment of The Overall Survival Rate of Cancer Using A Revised Taylor Expansion Algorithm- A Taiwanese Population-Based Survey for Breast And Colon Cancers." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3y7taq.

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博士<br>中臺科技大學<br>醫學影像暨放射科學系暨研究所<br>107<br>This paper explores the overall survival (OS) analysis using the Taylor expansion algorithm to give different interpretations of the survival curve under different stages of cancer with different treatments. Breast and colon cancers were selected examples for in-depth discussion. The proposed speculation was based on the theory of the hit and target model and make use of the Taylor expansion algorithm applied in Taiwanese population-based survey. The overall survival (OS) is the most commonly used assessment indicator for survival analysis, also calle
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20

"Language induction using population-based algorithms." Tulane University, 1994.

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Deterministic automata are induced from sample strings using a population based algorithm. Deterministic finite state automata are induced from regular languages, deterministic pushdown automata are induced from context free languages, and deterministic Turing machines are induced from regular languages, context free languages, and context sensitive languages. The algorithm is a variation of genetic algorithms using tree shaped chromosomes to represent the transition tables of the various automata. When Turing machines are induced, they are encapsulated and are available to subsequent inductio
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21

Lin, Yuen-Jen, and 林遠任. "Improving the Exponential Population Scheme for Model-Based Genetic Algorithms." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/ykmjrg.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>106<br>There are some parameters required to be tuned in early development of genetic algorithms. The tuning process is difficult for inexperienced users. In modern model-based genetic algorithms (MBGAs), most of these parameters are pre-determined, and therefore recent research concerning parameterless genetic algorithms targets at population size. This work is based on the exponential population scheme (EPS), which doubles the population until the solutions are satisfactory and is applicable to MBGAs without modifying their internal processes. In the thesis, three
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22

Lee, Zne-Jung, and 李仁鐘. "Population-Based Search Algorithms with Heuristics for Weapon-Target Assignment Problems." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/03195875105801572896.

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博士<br>國立臺灣科技大學<br>電機工程系<br>90<br>In this dissertation, population-based search algorithms with heuristics for weapon-target assignment (WTA) problems are proposed. WTA problems, known as NP-complete problems, are optimization problems, which are to find solutions that minimize the expected damage of own-force assets under the constraints of proper assignment of weapons to targets. Classical methods for solving WTA problems usually result in exponential computational complexities when the numbers of the considered weapon or target are large. In our study, two population-based search algorithms
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23

Guntsch, Michael, and Martin Middendorf. "Solving Multi-Criteria Optimization Problems with Population-Based ACO." 2003. https://ul.qucosa.de/id/qucosa%3A32897.

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In this paper a Population-based Ant Colony Optimization approach is proposed to solve multi-criteria optimization problems where the population of solutions is chosen from the set of all non-dominated solutions found so far. We investigate different maximum sizes for this population. The algorithm employs one pheromone matrix for each type of optimization criterion. The matrices are derived from the chosen population of solutions, and can cope with an arbitrary number of criteria. As a test problem, Single Machine Total Tardiness with changeover costs is used.
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24

Santos, Pedro Manuel Vieira dos. "Reconfigurable Custom Computing for Population-Based Optimization Metaheuristics: Accelerating Genetic Algorithms with FPGAs." Doctoral thesis, 2015. https://repositorio-aberto.up.pt/handle/10216/79984.

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Santos, Pedro Manuel Vieira dos. "Reconfigurable Custom Computing for Population-Based Optimization Metaheuristics: Accelerating Genetic Algorithms with FPGAs." Tese, 2015. https://repositorio-aberto.up.pt/handle/10216/79984.

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26

Wang, Leuo-Hong, and 王柳鋐. "Molecular Binding in Structure-based Drug Design: a Case Study of the Population-based Annealing Genetic Algorithms." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/80169844233632971485.

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博士<br>國立臺灣大學<br>資訊工程學系<br>85<br>In the past two decades, structure-based drug design has received increasing attention from research institutions and the pharmaceutical industry. Traditionally, each new drug requires 6-12 years to bring it from discovery to market. Such a lengthy drug discovery process is actually composed of several steps. These steps include finding good starting molecular structures for optimization, refining the starting molecular structures to generate potential drugs, biologically t
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27

Lockett, Alan Justin. "General-purpose optimization through information maximization." Thesis, 2012. http://hdl.handle.net/2152/ETD-UT-2012-05-5459.

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The primary goal of artificial intelligence research is to develop a machine capable of learning to solve disparate real-world tasks autonomously, without relying on specialized problem-specific inputs. This dissertation suggests that such machines are realistic: If No Free Lunch theorems were to apply to all real-world problems, then the world would be utterly unpredictable. In response, the dissertation proposes the information-maximization principle, which claims that the optimal optimization methods make the best use of the information available to them. This principle results in
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Kaelo, Professor. "Some Population Set-Based Methods for Unconstrained Global Optimization." Thesis, 2006. http://hdl.handle.net/10539/1771.

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Student Number : 0214677F - PhD thesis - School of Camputational and Applied Mathematics - Faculty of Science<br>Many real-life problems are formulated as global optimization problems with continuous variables. These problems are in most cases nonsmooth, nonconvex and often simulation based, making gradient based methods impossible to be used to solve them. Therefore, ef#2;cient, reliable and derivative-free global optimization methods for solving such problems are needed. In this thesis, we focus on improving the ef#2;ciency and reliability of some global optimization methods. In part
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