Relevant bibliographies by topics / Method of differential evolution / Dissertations / Theses
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Dissertations / Theses on the topic 'Method of differential evolution'

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Published: 28 May 2022
Last updated: 18 July 2025

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1

von, Glehn Ingrid. "A closest point penalty method for evolution equations on surfaces." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:29385f90-b927-4151-b5df-cf877cef00ef.

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This thesis introduces and analyses a numerical method for solving time-dependent partial differential equations (PDEs) on surfaces. This method is based on the closest point method, and solves the surface PDE by solving a suitably chosen equation in a band surrounding the surface. As it uses an implicit closest point representation of the surface, the method has the advantages of being simple to implement for very general surfaces, and amenable to discretization with a broad class of numerical schemes. The method proposed in this work introduces a new equation in the embedding space, which sa
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2

Maizurna, Isna. "Semigroup methods for degenerate cauchy problems and stochastic evolution equations /." Title page, abstract and contents only, 1999. http://web4.library.adelaide.edu.au/theses/09PH/09phm2328.pdf.

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3

Timmerman, Mattijs. "Optimization methods for nesting problems." Thesis, Högskolan Väst, Avd för automation och datateknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-5470.

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Nesting problems have been present for as long as mankind exists. Present days these problems occur in many different industries, e.g. textile, paper, wood, metal and glass industry. These industries produce massive amounts of products to answer the global demand. To minimize the material waste making these products, a good cutting and packing layout is beneficial. The last three decades, researchers have focused on developing methods to solve these problems through computing, instead of solving them manually. Many possible solutions have been found, each method focusing on the specifications
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Johnsen, Pernilla. "Homogenization of Partial Differential Equations using Multiscale Convergence Methods." Licentiate thesis, Mittuniversitetet, Institutionen för matematik och ämnesdidaktik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42036.

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The focus of this thesis is the theory of periodic homogenization of partial differential equations and some applicable concepts of convergence. More precisely, we study parabolic problems exhibiting both spatial and temporal microscopic oscillations and a vanishing volumetric heat capacity type of coefficient. We also consider a hyperbolic-parabolic problem with two spatial microscopic scales. The tools used are evolution settings of multiscale and very weak multiscale convergence, which are extensions of, or closely related to, the classical method of two-scale convergence. The novelty of th
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Zhou, Bo. "The existence of bistable stationary solutions of random dynamical systems generated by stochastic differential equations and random difference equations." Thesis, Loughborough University, 2009. https://dspace.lboro.ac.uk/2134/14255.

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In this thesis, we study the existence of stationary solutions for two cases. One is for random difference equations. For this, we prove the existence and uniqueness of the stationary solutions in a finite-dimensional Euclidean space Rd by applying the coupling method. The other one is for semi linear stochastic evolution equations. For this case, we follows Mohammed, Zhang and Zhao [25]'s work. In an infinite-dimensional Hilbert space H, we release the Lipschitz constant restriction by using Arzela-Ascoli compactness argument. And we also weaken the globally bounded condition for F by applyin
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Inclan, Eric. "The Development of a Hybrid Optimization Algorithm for the Evaluation and Optimization of the Asynchronous Pulse Unit." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1582.

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The effectiveness of an optimization algorithm can be reduced to its ability to navigate an objective function’s topology. Hybrid optimization algorithms combine various optimization algorithms using a single meta-heuristic so that the hybrid algorithm is more robust, computationally efficient, and/or accurate than the individual algorithms it is made of. This thesis proposes a novel meta-heuristic that uses search vectors to select the constituent algorithm that is appropriate for a given objective function. The hybrid is shown to perform competitively against several existing hybrid and non-
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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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Lima, Tiago Pessoa Ferreira de. "An authomatic method for construction of multi-classifier systems based on the combination of selection and fusion." Universidade Federal de Pernambuco, 2013. https://repositorio.ufpe.br/handle/123456789/12457.

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Submitted by João Arthur Martins (joao.arthur@ufpe.br) on 2015-03-12T17:38:41Z No. of bitstreams: 2 Dissertaçao Tiago de Lima.pdf: 1469834 bytes, checksum: 95a0326778b3d0f98bd35a7449d8b92f (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5)<br>Approved for entry into archive by Daniella Sodre (daniella.sodre@ufpe.br) on 2015-03-13T14:23:38Z (GMT) No. of bitstreams: 2 Dissertaçao Tiago de Lima.pdf: 1469834 bytes, checksum: 95a0326778b3d0f98bd35a7449d8b92f (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5)<br>Made available in DSpace
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Xu, Ke. "INTELLIGENT METHODS FOR OPTIMUM ONLINE ADAPTIVE COORDINATION OF OVERCURRENT RELAYS." UKnowledge, 2018. https://uknowledge.uky.edu/ece_etds/127.

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During the operation in a modern power distribution system, some abnormal events may happen, such as over-voltage, faults, under-frequency and overloading, and so on. These abnormal events may cause a power outage in a distribution system or damages on the equipment in a distribution system. Hence these abnormal events should be identified and isolated by protection systems as quickly as possible to make sure we can maintain a stable and reliable distribution system to supply adequate electric power to the largest number of consumers as we can. To sum up, we need stable and reliable protection
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10

Hodgkinson, Arran. "Mathematical Methods for Modelling Biological Heterogeneity." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS119.

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Les processus biologiques sont des phénomènes complexes, multi-échelles, présentant une hétérogénéité importante à travers l’espace, la structure et la fonction. De plus, ils impliquent des événements fortement corrélés et présentent des boucles de rétroaction à travers les échelles. Dans cette thèse, nous utilisons des représentations spatio-structuro-temporelles en grande dimension pour étudier l'hétérogénéité biologique à travers l'espace, la fonction biologique et le temps, et appliquons cette méthode à divers problèmes importants en biologie et en clinique.Nous commençons par introduire u
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Wolmuth, Leidy Diane. "Modelagem e simulações do comportamento evolutivo de poluentes em corpos aquaticos de grande extensão : o caso da represa do rio Manso." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307277.

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Orientador: João Frederico da Costa Azevedo Meyer<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica<br>Made available in DSpace on 2018-08-14T16:35:21Z (GMT). No. of bitstreams: 1 Wolmuth_LeidyDiane_M.pdf: 1357363 bytes, checksum: 1c7aa0f871b134a5d1313bab203cc5c0 (MD5) Previous issue date: 2009<br>Resumo: Este trabalho modela o comportamento evolutivo de poluentes em corpos aquáticos de grande extensão. O tratamento é bidimensional na variável espacial, que descreve a superfície de um lago ou represa, por exemplo, e a
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Drury, R. G. "Trajectory generation for autonomous unmanned aircraft using inverse dynamics." Thesis, Cranfield University, 2010. http://dspace.lib.cranfield.ac.uk/handle/1826/5583.

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The problem addressed in this research is the in-flight generation of trajectories for autonomous unmanned aircraft, which requires a method of generating pseudo-optimal trajectories in near-real-time, on-board the aircraft, and without external intervention. The focus of this research is the enhancement of a particular inverse dynamics direct method that is a candidate solution to the problem. This research introduces the following contributions to the method. A quaternion-based inverse dynamics model is introduced that represents all orientations without singularities, permits smooth interpo
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13

Loubiere, Peio. "Amélioration des métaheuristiques d'optimisation à l'aide de l'analyse de sensibilité." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1051/document.

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L'optimisation difficile représente une classe de problèmes dont la résolution ne peut être obtenue par une méthode exacte en un temps polynomial.Trouver une solution en un temps raisonnable oblige à trouver un compromis quant à son exactitude.Les métaheuristiques sont une classe d'algorithmes permettant de résoudre de tels problèmes, de manière générique et efficiente (i.e. trouver une solution satisfaisante selon des critères définis: temps, erreur, etc.).Le premier chapitre de cette thèse est notamment consacré à la description de cette problématique et à l'étude détaillée de deux familles
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14

Yilmaz, Halis. "Evolution equations for differential invariants." Thesis, University of Glasgow, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274288.

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15

Silva, Eduardo Krempser da. "Differential evolution for constrained optimization problems." Laboratório Nacional de Computação Científica, 2009. http://www.lncc.br/tdmc/tde_busca/arquivo.php?codArquivo=188.

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Optimization is a large area of knowledge concerned with the need of a better use of resources and activities, becoming indispensable in the solution of several problems which arise from the study and formulation of real-world problems. Furthermore, the constraints that must be respected for each situation introduce in the methodologies of optimization an additional complication. Differential Evolution, which in its original formulation is applied only to unconstrained optimization problems in continuous space, also provides good results when applied to constrained optimization with discrete a
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Farah, Abdulkadir. "Differential evolution algorithms for network optimization." Thesis, University of Reading, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602400.

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Many real world optimization problems are difficult to solve, therefore, when solving such problems it is wise to employ efficient optimization algorithms which are capable of handling the problem complexities and of finding optimal or near optimal solutions within a reasonable time and without using excessive computational resources. The objective of this research is to develop Differential Evolution (DE) algorithms with improved performance capable of solving difficult and challenging global constrained and unconstrained optimization problems, as well as extending the application of the thes
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Nguyen, Thieu-Huy. "Functional partial differential equations and evolution semigroups." [S.l.] : [s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=973911344.

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18

Cedeño-Maldonado, José R. "Differential evolution based optimal power flow algorithm /." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486402288260595.

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19

Leon, Miguel. "Enhancing Differential Evolution Algorithm for Solving Continuous Optimization Problems." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-33466.

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Differential Evolution (DE) has become one of the most important metaheuristics during the recent years, obtaining attractive results in solving many engineering optimization problems. However, the performance of DE is not always strong when seeking optimal solutions. It has two major problems in real world applications. First, it can easily get stuck in a local optimum or fail to generate better solutions before the population has converged. Secondly, its performance is significantly influenced by the control parameters, which are problem dependent and which vary in different regions of space
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20

Enaganti, Srujan Kumar. "Solving correlation matrix completion problems using parallel differential evolution." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/30302.

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Matrix Completion problems have been receiving increased attention due to their varied applicability in different domains. Correlation matrices arise often in studying multiple streams of time series data like technical analysis of stock market data. Often some of the values in the matrix are unknown and some reasonable replacements have to be found at the earliest opportunity to avert an unwanted consequence or keep up the pace in the business. After looking to background research related to solving this problem, we propose a new parallel technique that can solve general correlation matrix co
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Christoph, Raab. "Reconstruction of PINGU data with a Differential Evolution Minimizer." Thesis, Uppsala universitet, Högenergifysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-214617.

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The Precision IceCube Next Generation Upgrade (PINGU) is supposed to have an energy threshold below 10 in order to resolve the neutrino mass hierarchy. In order to reconstruct the energy and direction of neutrinos interacting in this array, producing both a hadronic cascade and a muon track, advanced reconstruction methods need to be employed. A class of these seeks to maximize a complicated likelihood function within an 8-dimensional parameter space describing the event, and requires sophisticated minimizers to achieve the necessary resolution in a reasonable time. In this report, a pre-exist
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Dawar, Deepak. "Adaptive Differential Evolution and its Application to Machine Vision." Diss., North Dakota State University, 2016. http://hdl.handle.net/10365/25732.

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Over recent years, Evolutionary Algorithms (EA) have emerged as a practical approach for solving hard optimization problems ubiquitously presented in real life. The inherent advantage of EA over other types of numerical optimization methods lies in the fact that they require much less or no prior knowledge of the objective function. Differential Evolution (DE) has emerged as a highly competitive and powerful real parameter optimizer in the diverse community of evolutionary algorithms. The study of this dissertation is focused on two main approaches. The first approach focuses on studying and i
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Mulumba, Tshina Fa. "Application of differential evolution to power system stabilizer design." Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/12026.

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Includes synopsis.<br>Includes bibliographical references.<br>In recent years, many Evolutionary Algorithms (EAs) such as Genetic Algorithms (GAs) have been proposed to optimally tune the parameters of the PSS. GAs are population based search methods inspired by the mechanism of evolution and natural genetic. Despite the fact that GAs are robust and have given promising results in many applications, they still have some drawbacks. Some of these drawbacks are related to the problem of genetic drift in GA which restricts the diversity in the population. ... To cope with the above mentioned drawb
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Nguyen, Thi. "On the Evolution of Virulence." CSUSB ScholarWorks, 2014. https://scholarworks.lib.csusb.edu/etd/91.

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The goal of this thesis is to study the dynamics behind the evolution of virulence. We examine first the underlying mechanics of linear systems of ordinary differential equations by investigating the classification of fixed points in these systems, then applying these techniques to nonlinear systems. We then seek to establish the validity of a system that models the population dynamics of uninfected and infected hosts---first with one parasite strain, then n strains. We define the basic reproductive ratio of a parasite, and study its relationship to the evolution of virulence. Lastly, we inves
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Akman, Makbule. "Differential Quadrature Method For Time-dependent Diffusion Equation." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1224559/index.pdf.

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This thesis presents the Differential Quadrature Method (DQM) for solving time-dependent or heat conduction problem. DQM discretizes the space derivatives giving a system of ordinary differential equations with respect to time and the fourth order Runge Kutta Method (RKM) is employed for solving this system. Stabilities of the ordinary differential equations system and RKM are considered and step sizes are arranged accordingly. The procedure is applied to several time dependent diffusion problems and the solutions are presented in terms of graphics comparing with the exact solutions. Thi
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Mansoora, Abida. "The sequential spectral method for integro-differential equations /." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38230.

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Using the Galerkin method to solve nonlinear integro-differential equations of elliptic or parabolic type one needs to solve the resulting nonlinear systems of algebraic or ordinary differential equations. To solve these equations with Newtons method or a variant thereof can be very difficult and one needs a good initial guess for the methods to converge. Also there might be multiple solutions and it is virtually impossible to track all of them. In addition it is hard to study the parameter dependence of solutions. We developed a remedy for these problems by developing the sequential spectral
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Yang, Jie. "Solving Partial Differential Equations by Taylor Meshless Method." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0032/document.

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Le but de cette thèse est de développer une méthode numérique simple, robuste, efficace et précise pour résoudre des problèmes d'ingénierie de grande taille à partir de la méthode Taylor Meshless (TMM) et fournir de nouvelles idées principales de TMM est d'utiliser comme fonctions de forme des polynômes d'ordre élevé qui sont des solutions approchées de l'EDP. Ainsi la discrétisation ne concerne que la frontière. Les coefficients de ces fonctions de forme sont obtenus en discrétisant les conditions aux limites par des procédures de collocation associées à la méthode des moindres carrés. TMM es
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Ugail, Hassan, and N. Kirmani. "Method of surface reconstruction using partial differential equations." WSEAS, 2006. http://hdl.handle.net/10454/2750.

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Hosseini, Ali Abadi M. "The Tau method in the solution of differential inclusions and nonlinear partial differential equations." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/47111.

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Zangeneh, Bijan Z. "Semilinear stochastic evolution equations." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/31117.

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Let H be a separable Hilbert space. Suppose (Ω, F, Ft, P) is a complete stochastic basis with a right continuous filtration and {Wt,t ∈ R} is an H-valued cylindrical Brownian motion with respect to {Ω, F, Ft, P). U(t, s) denotes an almost strong evolution operator generated by a family of unbounded closed linear operators on H. Consider the semilinear stochastic integral equation [formula omitted] where • f is of monotone type, i.e., ft(.) = f(t, w,.) : H → H is semimonotone, demicon-tinuous, uniformly bounded, and for each x ∈ H, ft(x) is a stochastic process which satisfies certain measur
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Sum-Im, Thanathip. "A novel differential evolution algorithmic approach to transmission expansion planning." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3219.

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Nowadays modern electric power systems consist of large-scale and highly complex interconnected transmission systems, thus transmission expansion planning (TEP) is now a significant power system optimisation problem. The TEP problem is a large-scale, complex and nonlinear combinatorial problem of mixed integer nature where the number of candidate solutions to be evaluated increases exponentially with system size. The accurate solution of the TEP problem is essential in order to plan power systems in both an economic and efficient manner. Therefore, applied optimisation methods should be suffic
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Thuy, N. T. P., R. Pendyala, Nejat Rahmanian, and N. Marneni. "Heat exchanger network optimization by differential evolution method." 2014. http://hdl.handle.net/10454/18554.

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No<br>The synthesis of heat exchanger network (HEN) is a comprehensive approach to optimize energy utilization in process industry. Recent developments in HEN synthesis (HENS) present several heuristic methods, such as Simulated Annealing (SA), Genetic Algorithm (GA), and Differential Evolution (DE). In this work, DE method for synthesis and optimization of HEN has been presented. Using DE combined with the concept of super-targeting, the ΔTmin optimization is determined. Then DE algorithm is employed to optimize the global cost function including the constraints, such as heat balance, the tem
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Kajee-Bagdadi, Zaakirah. "Differential evolution algorithms for constrained global optimization." Thesis, 2008. http://hdl.handle.net/10539/4733.

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In this thesis we propose four new methods for solving constrained global optimization problems. The first proposed algorithm is a differential evolution (DE) algorithm using penalty functions for constraint handling. The second algorithm is based on the first DE algorithm but also incorporates a filter set as a diversification mechanism. The third algorithm is also based on DE but includes an additional local refinement process in the form of the pattern search (PS) technique. The last algorithm incorporates both the filter set and PS into the DE algorithm for constrained global optimiz
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Ching, Wang Yen, and 王彥欽. "Differential Evolution to Estimate Software Effort with Ward’s method Clustering." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/54313320611924309615.

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碩士<br>大同大學<br>資訊工程學系(所)<br>99<br>In Information Technology Industry, how to accurately estimate one project’s spending in the cost and works always plays a very important role in software companies. Therefore, this research via Ward method clustering algorithm and applies differential evolution, a new algorithm, to estimate the optimal volume of works in software projects to acquire biggest benefit in the cost. In algorithm, generations of chromosomes firstly use Pred and MMRE to figure out their fitness then keep renewing their values by Mutation, Crossover, and Selection to substitute the ol
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Cheng, Meng-Chia, and 鄭孟佳. "Power Systems Reactive Power Dispatch Using a Hybrid Differential Evolution Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/41480999861567779020.

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碩士<br>崑山科技大學<br>電機工程研究所<br>99<br>This thesis applies a hybrid differential evolution (HDE) method to the optimal reactive power dispatch (ORPD) problem. Based on the minimization of active power transmission losses or the other objectives, the reactive power dispatch is to adjust control variables subjected to some operating constraints. Basically, it is classically a mixed-integer and nonlinear programming problem. Its objectives not only posses nonlinear characteristic, but also exist multiple local optimum. Since HDE is an excellent optimization tool, it is very suitable to deal with the OR
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Dolo, Kgaugelo Moses. "Differential evolution technique on weighted voting stacking ensemble method for credit card fraud detection." Diss., 2019. http://hdl.handle.net/10500/26758.

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Differential Evolution is an optimization technique of stochastic search for a population-based vector, which is powerful and efficient over a continuous space for solving differentiable and non-linear optimization problems. Weighted voting stacking ensemble method is an important technique that combines various classifier models. However, selecting the appropriate weights of classifier models for the correct classification of transactions is a problem. This research study is therefore aimed at exploring whether the Differential Evolution optimization method is a good approach for defining t
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Maizurna, Isna. "Semigroup methods for degenerate cauchy problems and stochastic evolution equations / Isna Maizurna." Thesis, 1999. http://hdl.handle.net/2440/19449.

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Michoski, Craig E. "Evolution equations in physical chemistry." Thesis, 2009. http://hdl.handle.net/2152/ETD-UT-2009-05-54.

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We analyze a number of systems of evolution equations that arise in the study of physical chemistry. First we discuss the well-posedness of a system of mixing compressible barotropic multicomponent flows. We discuss the regularity of these variational solutions, their existence and uniqueness, and we analyze the emergence of a novel type of entropy that is derived for the system of equations. Next we present a numerical scheme, in the form of a discontinuous Galerkin (DG) finite element method, to model this compressible barotropic multifluid. We find that the DG method provides stable and
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Chen, Yu-Zhen, and 陳宥臻. "Reliability Assessment Based on Progressively Type-I Interval Censored Measurements Using Genetic Algorithm and Differential Evolution Methods." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/56386502526090796255.

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碩士<br>淡江大學<br>統計學系碩士班<br>103<br>To the advantage of progressively censoring method that allow experimenters to observe more extreme lifetimes of products and the administration convenience of the interval censoring method, this thesis evaluates the performance of difference algorithms, the quasi-Newton method, genetic algorithm method and differential evolution methods for maximum likelihood estimates based on the progressively type I interval censored samples for the Burr type XII distribution. An intensive simulation study was conduct for comparing the estimation performance of the quasi-New
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Сумко, Віталій Володимирович, та Vitaliy Sumko. "Розробка експертної системи для оптимізації споживання енергії в електричних мережах на основі методу диференціальної еволюції". Master's thesis, 2022. http://elartu.tntu.edu.ua/handle/lib/37918.

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Кваліфікаційна робота присвячена розробці експертної системи для оптимізації споживання енергії електрообладнанням в електричних мережах на основі методу диференціальної еволюції. Дослідження спрямоване на підбір електрообладнання, котре дає змогу оптимізувати приведені витрати шляхом зменшення втрат електроенергії відповідно до алгоритму прийняття рішень вибору електроустаткування. Проведено аналіз джерел з розробки та впровадження експертних систем у різних галузях науки; з’ясовано, що такий тип програмного рішення найефективніший при застосуванні у вузько предметних областях; описано алгори
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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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42

Rahnamayan, Shahryar. "Opposition-Based Differential Evolution." Thesis, 2007. http://hdl.handle.net/10012/2784.

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Evolutionary algorithms (EAs) are well-established techniques to approach those problems which for the classical optimization methods are difficult to solve. Tackling problems with mixed-type of variables, many local optima, undifferentiable or non-analytical functions are some examples to highlight the outstanding capabilities of the evolutionary algorithms. Among the various kinds of evolutionary algorithms, differential evolution (DE) is well known for its effectiveness and robustness. Many comparative studies confirm that the DE outperforms many other optimizers. Finding more accurate solu
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Hunag, Shin-chia, and 黃信嘉. "Dynamic Clustering Using Differential Evolution." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/21178749888377219637.

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碩士<br>大同大學<br>資訊工程學系(所)<br>96<br>Data clustering is one of the important issues on the data mining techniques which is the process of considering as the number of cluster and the center of cluster. Most of data clustering algorithms are prior known of the number of cluster but dynamic clustering is able to find the optimal number of cluster and center of cluster dynamically by algorithms. This research is used differential evolution algorithm to perform data clustering which is called as dynamic clustering using differential evolution (DCDE). This algorithm is accessed the number of cluster of
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Chien, Wan-Jou, and 簡宛柔. "A Novel Differential Evolution Algorithm with co-evolution strategy." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/42161994725526399905.

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碩士<br>中原大學<br>資訊管理研究所<br>98<br>Differential evolution, termed DE, is a novel and rapidly developed evolution computation in recent year. There are some advantages of DE, including simple structure, easy use and rapid convergence speed. Besides, DE can be also applied on complex optimization problem. However, there are some problems, such as premature convergence and stagnation, remaining in DE algorithm. To overcome those disadvantages, a different method was proposed, named CO-DE, by combining with a simple co-evolutionary model and reset mechanism. Thus, CO-DE can maintain appropriate swarm
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Tseng, Ko-Ying, and 曾科穎. "Modified Differential Evolution for Structural Optimization." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/31731599346536819939.

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博士<br>大同大學<br>機械工程學系(所)<br>98<br>Differential evolution (DE) is a heuristic optimization method used to solve many optimization problems in real-valued search space. It has the advantage of incorporating a relatively simple and efficient form of mutation and crossover. In this study, two modified differential evolution algorithm, adaptive multi-population differential evolution and modified binary differential evolution, have been developed for dealing with different types of optimization problems. The adaptive multi-population differential evolution (AMPDE), including a proposed penalty-based
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Raghunathan, T. "Differential Evolution Based Interceptor Guidance Law." Thesis, 2011. https://etd.iisc.ac.in/handle/2005/2014.

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Kinematics based guidance laws like the proportional navigation (PN) and many other linear optimal guidance laws perform well in near-collision course conditions. These have been studied thoroughly in the literature from all aspects, ranging from optimality to capturability, for planar or two dimensional interceptor-target engagements, and to a lesser extent, for three dimensional engagements. But guidance in widely off-collision course conditions like high initial heading errors has been relatively less studied. This is probably due to the inherently high nonlinearity of the problem, which ma
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47

Raghunathan, T. "Differential Evolution Based Interceptor Guidance Law." Thesis, 2011. http://etd.iisc.ernet.in/handle/2005/2014.

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Kinematics based guidance laws like the proportional navigation (PN) and many other linear optimal guidance laws perform well in near-collision course conditions. These have been studied thoroughly in the literature from all aspects, ranging from optimality to capturability, for planar or two dimensional interceptor-target engagements, and to a lesser extent, for three dimensional engagements. But guidance in widely off-collision course conditions like high initial heading errors has been relatively less studied. This is probably due to the inherently high nonlinearity of the problem, which ma
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Rogalsky, Timothy P. "Acceleration of differential evolution for aerodynamic design." 2004. http://hdl.handle.net/1993/15752.

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Guo, Ching-Yi, and 郭青沂. "Improved Differential Evolution Algorithm and Its Applications." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/gkkc6z.

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碩士<br>國立高雄第一科技大學<br>系統資訊與控制研究所<br>96<br>In this thesis, we proposed two improved differential evolution (DE) algorithms, which are, respectively, called Taguchi-mutation differential evolution (TMDE) algorithm and Taguchi-crossover differential evolution (TCDE) algorithm. The proposed TMDE is a method of combining the tradition DE with the Taguchi method into mutation, and TCDE is a method of using sliding levels of Taguchi method into crossover. On the other hand, the biggest problem in finding optimal solutions is that we cannot know the range of searching. Hence, in this thesis, we incorpor
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Chen, CHIH-YUNG, and 陳智勇. "Using Discrete Differential Evolution for Portfolio Optimization." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/3767z5.

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碩士<br>大同大學<br>資訊經營學系(所)<br>102<br>In the portfolio optimization problem, return and risk factors are considered at the same time, thus the problem is a multi-objective problem. When the number of stocks is large, the complexity of the problem becomes high and it consumes much more CPU time to solve it. Recently some researchers have utilized particle swarm optimization (PSO) and differential evolution (DE) to solve the portfolio optimization problem. Unfortunately, their CPU usage becomes high as the sizes of test problems increase. This study tries to overcome this problem. A discrete differe
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