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 Title
 Performance analysis of the genetic algorithm and its applications.
 Creator
 Liu, Xinggang., Florida Atlantic University, Zhuang, Hanqi, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

Research and applications of genetic algorithms have become increasingly important in a wide variety of scientific fields. In this thesis, we present an empirical analysis of genetic algorithms in the function optimization area. As a focus of our research, a novel empirical analysis approach to various genetic algorithms is provided. The research starts from the survey of current trends in genetic algorithms, followed by exploring the characteristics of the simple genetic algorithm, the...
Show moreResearch and applications of genetic algorithms have become increasingly important in a wide variety of scientific fields. In this thesis, we present an empirical analysis of genetic algorithms in the function optimization area. As a focus of our research, a novel empirical analysis approach to various genetic algorithms is provided. The research starts from the survey of current trends in genetic algorithms, followed by exploring the characteristics of the simple genetic algorithm, the modified genetic algorithm and hybridized genetic algorithm. A number of typical function optimization problems are solved by these genetic algorithms. Ample empirical data associated with various modifications to the simple genetic algorithm is also provided. Results from this research can be used to assist practitioners in their applications of genetic algorithms.
Show less  Date Issued
 1995
 PURL
 http://purl.flvc.org/fcla/dt/15210
 Subject Headings
 Genetic algorithms, Combinatorial optimization
 Format
 Document (PDF)
 Title
 Optimal planning of robot calibration experiments by genetic algorithms.
 Creator
 Huang, Weizhen., Florida Atlantic University, Wu, Jie
 Abstract/Description

In this thesis work, techniques developed in the science of genetic computing is applied to solve the problem of planning a robot calibration experiment. Robot calibration is a process by the robot accuracy is enhanced through modification of its control software. The selection of robot measurement configurations is an important element in successfully completing a robot calibration experiment. A classical genetic algorithm is first customized for a type of robot measurement configuration...
Show moreIn this thesis work, techniques developed in the science of genetic computing is applied to solve the problem of planning a robot calibration experiment. Robot calibration is a process by the robot accuracy is enhanced through modification of its control software. The selection of robot measurement configurations is an important element in successfully completing a robot calibration experiment. A classical genetic algorithm is first customized for a type of robot measurement configuration selection problem in which the robot workspace constraints are defined in terms of robot joint limits. The genetic parameters are tuned in a systematic way to greatly enhance the performance of the algorithm. A recruitoriented genetic algorithm is then proposed, together with new genetic operators. Examples are also given to illustrate the concepts of this new genetic algorithm. This new algorithm is aimed at solving another type of configuration selection problem, in which not all points in the robot workspace are measurable by an external measuring device. Extensive simulation studies are conducted for both classical and recruitoriented genetic algorithms, to examine the effectiveness of these algorithms.
Show less  Date Issued
 1995
 PURL
 http://purl.flvc.org/fcla/dt/15186
 Subject Headings
 Genetic algorithms, RobotsCalibration, Combinatorial optimization
 Format
 Document (PDF)
 Title
 A novel optimization algorithm and other techniques in medicinal chemistry.
 Creator
 Santos, Radleigh G., Charles E. Schmidt College of Science, Department of Mathematical Sciences
 Abstract/Description

In this dissertation we will present a stochastic optimization algorithm and use it and other mathematical techniques to tackle problems arising in medicinal chemistry. In Chapter 1, we present some background about stochastic optimization and the Accelerated Random Search (ARS) algorithm. We then present a novel improvement of the ARS algorithm, DIrected Accelerated Random Search (DARS), motivated by some theoretical results, and demonstrate through numerical results that it improves upon...
Show moreIn this dissertation we will present a stochastic optimization algorithm and use it and other mathematical techniques to tackle problems arising in medicinal chemistry. In Chapter 1, we present some background about stochastic optimization and the Accelerated Random Search (ARS) algorithm. We then present a novel improvement of the ARS algorithm, DIrected Accelerated Random Search (DARS), motivated by some theoretical results, and demonstrate through numerical results that it improves upon ARS. In Chapter 2, we use DARS and other methods to address issues arising from the use of mixturebased combinatorial libraries in drug discovery. In particular, we look at models associated with the biological activity of these mixtures and use them to answer questions about sensitivity and robustness, and also present a novel method for determining the integrity of the synthesis. Finally, in Chapter 3 we present an indepth analysis of some statistical and mathematical techniques in combinatorial chemistry, including a novel probabilistic approach to using structural similarity to predict the activity landscape.
Show less  Date Issued
 2012
 PURL
 http://purl.flvc.org/FAU/3352830
 Subject Headings
 Drugs, Design, Mathematical models, Combinatorial optimization, Combinatorial chemistry, Genetic algorithms, Mathematical optimization, Stochastic processes
 Format
 Document (PDF)
 Title
 General monotonicity, interpolation of operators, and applications.
 Creator
 Grigoriev, Stepan M., Sagher, Yoram, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Mathematical Sciences
 Abstract/Description

Assume that {φn} is an orthonormal uniformly bounded (ONB) sequence of complexvalued functions de ned on a measure space (Ω,Σ,µ), and f ∈ L1(Ω,Σ,µ). Let be the Fourier coefficients of f with respect to {φn} . R.E.A.C. Paley proved a theorem connecting the Lpnorm of f with a related norm of the sequence {cn}. Hardy and Littlewood subsequently proved that Paley’s result is best possible within its context. Their results were generalized by Dikarev, Macaev, Askey, Wainger, Sagher, and later by...
Show moreAssume that {φn} is an orthonormal uniformly bounded (ONB) sequence of complexvalued functions de ned on a measure space (Ω,Σ,µ), and f ∈ L1(Ω,Σ,µ). Let be the Fourier coefficients of f with respect to {φn} . R.E.A.C. Paley proved a theorem connecting the Lpnorm of f with a related norm of the sequence {cn}. Hardy and Littlewood subsequently proved that Paley’s result is best possible within its context. Their results were generalized by Dikarev, Macaev, Askey, Wainger, Sagher, and later by Tikhonov, Li yand, Booton and others.The present work continues the generalization of these results.
Show less  Date Issued
 2014
 PURL
 http://purl.flvc.org/fau/fd/FA00004290, http://purl.flvc.org/fau/fd/FA00004290
 Subject Headings
 Combinatorial optimization, Differential dynamical systems, Functions of complex variables, Inequalities (Mathematics), Nonsmooth optimization
 Format
 Document (PDF)
 Title
 Construction of combinatorial designs with prescribed automorphism groups.
 Creator
 Kolotoglu, Emre., Charles E. Schmidt College of Science, Department of Mathematical Sciences
 Abstract/Description

In this dissertation, we study some open problems concerning the existence or nonexistence of some combinatorial designs. We give the construction or proof of nonexistence of some Steiner systems, large sets of designs, and graph designs, with prescribed automorphism groups.
 Date Issued
 2013
 PURL
 http://purl.flvc.org/fcla/dt/3360795
 Subject Headings
 Combinatorial designs and configurations, Finite geometries, Curves, Algebraic, Automorphisms, Mathematical optimization, Steiner systems
 Format
 Document (PDF)
 Title
 CBRbased software quality models and quality of data.
 Creator
 Xiao, Yudong., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

The performance accuracy of software quality estimation models is influenced by several factors, including the following two important factors: performance of the prediction algorithm and the quality of data. This dissertation addresses these two factors, and consists of two components: (1) a proposed genetic algorithm (GA) based optimization of software quality models for accuracy enhancement, and (2) a proposed partitioning and rulebased filter (PRBF) for noise detection toward...
Show moreThe performance accuracy of software quality estimation models is influenced by several factors, including the following two important factors: performance of the prediction algorithm and the quality of data. This dissertation addresses these two factors, and consists of two components: (1) a proposed genetic algorithm (GA) based optimization of software quality models for accuracy enhancement, and (2) a proposed partitioning and rulebased filter (PRBF) for noise detection toward improvement of data quality. We construct a generalized framework of our embedded GAoptimizer, and instantiate the GAoptimizer for three optimization problems in software quality engineering: parameter optimization for casebased reasoning (CBR) models; module rank optimization for moduleorder modeling (MOM); and structural optimization for our multistrategy classification modeling approach, denoted RB2CBL. Empirical case studies using software measurement data from realworld software systems were performed for the optimization problems. The GAoptimization approaches improved software quality prediction accuracy, highlighting the practical benefits of using GA for solving optimization problems in software engineering. The proposed noise detection approach, PRBF, was empirically evaluated using data categorized into two classes. Empirical studies on artificially corrupted datasets and datasets with known (natural) noise demonstrated that PRBF can effectively detect both artificial and natural noise. The proposed filter is a stable and robust technique, and always provided optimal or nearoptimal noise detection results. In addition, it is applicable on datasets with nominal and numerical attributes, as well as those with missing values. The PRBF technique supports two methods of noise detection: class noise detection and costsensitive noise detection. The former is an easytouse method and does not need parameter settings, while the latter is suited for applications where each class has a specific misclassification cost. PRBF can also be used iteratively to investigate the two general types of data noise: attribute and class noise.
Show less  Date Issued
 2005
 PURL
 http://purl.flvc.org/fcla/dt/12141
 Subject Headings
 Computer softwareQuality control, Genetic programming (Computer science), Software engineering, Casebased reasoning, Combinatorial optimization, Computer network architecture
 Format
 Document (PDF)
 Title
 An Ant Inspired Dynamic Traffic Assignment for VANETs: Early Notification of Traffic Congestion and Traffic Incidents.
 Creator
 Arellano, Wilmer, Mahgoub, Imad, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
 Abstract/Description

Vehicular Ad hoc NETworks (VANETs) are a subclass of Mobile Ad hoc NETworks and represent a relatively new and very active field of research. VANETs will enable in the near future applications that will dramatically improve roadway safety and traffic efficiency. There is a need to increase traffic efficiency as the gap between the traveled and the physical lane miles keeps increasing. The Dynamic Traffic Assignment problem tries to dynamically distribute vehicles efficiently on the road...
Show moreVehicular Ad hoc NETworks (VANETs) are a subclass of Mobile Ad hoc NETworks and represent a relatively new and very active field of research. VANETs will enable in the near future applications that will dramatically improve roadway safety and traffic efficiency. There is a need to increase traffic efficiency as the gap between the traveled and the physical lane miles keeps increasing. The Dynamic Traffic Assignment problem tries to dynamically distribute vehicles efficiently on the road network and in accordance with their origins and destinations. We present a novel dynamic decentralized and infrastructureless algorithm to alleviate traffic congestions on road networks and to fill the void left by current algorithms which are either static, centralized, or require infrastructure. The algorithm follows an online approach that seeks stochastic user equilibrium and assigns traffic as it evolves in real time, without prior knowledge of the traffic demand or the schedule of the cars that will enter the road network in the future. The Reverse Online Algorithm for the Dynamic Traffic Assignment inspired by Ant Colony Optimization for VANETs follows a metaheuristic approach that uses reports from other vehicles to update the vehicle’s perceived view of the road network and change route if necessary. To alleviate the broadcast storm spontaneous clusters are created around traffic incidents and a threshold system based on the level of congestion is used to limit the number of incidents to be reported. Simulation results for the algorithm show a great improvement on travel time over routing based on shortest distance. As the VANET transceivers have a limited range, that would limit messages to reach at most 1,000 meters, we present a modified version of this algorithm that uses a rebroadcasting scheme. This rebroadcasting scheme has been successfully tested on roadways with segments of up to 4,000 meters. This is accomplished for the case of traffic flowing in a single direction on the roads. It is anticipated that future simulations will show further improvement when traffic in the other direction is introduced and vehicles travelling in that direction are allowed to use a store carry and forward mechanism.
Show less  Date Issued
 2016
 PURL
 http://purl.flvc.org/fau/fd/FA00004566, http://purl.flvc.org/fau/fd/FA00004566
 Subject Headings
 Vehicular ad hoc networks (Computer networks)Technological innovations., Routing protocols (Computer network protocols), Artificial intelligence., Intelligent transportation systems., Intelligent control systems., Mobile computing., Computer algorithms., Combinatorial optimization.
 Format
 Document (PDF)