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Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve
Scheduling For Space Tracking And Heterogeneous Sensor Environments, Gabriel H. Greve
Theses and Dissertations
This dissertation draws on the fields of heuristic and meta-heuristic algorithm development, resource allocation problems, and scheduling to address key Air Force problems. The world runs on many schedules. People depend upon them and expect these schedules to be accurate. A process is needed where schedules can be dynamically adjusted to allow tasks to be completed efficiently. For example, the Space Surveillance Network relies on a schedule to track objects in space. The schedule must use sensor resources to track as many high-priority satellites as possible to obtain orbit paths and to warn of collision paths. Any collisions that occurred …
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …
Collaborative Uav Planning, Mapping, And Exploration In Gps-Denied Environments, Jacob Moroni Olson
Collaborative Uav Planning, Mapping, And Exploration In Gps-Denied Environments, Jacob Moroni Olson
Theses and Dissertations
The use of multirotor UAVs to map GPS-degraded environments is useful for many purposes ranging from routine structural inspections to post-disaster exploration to search for survivors and evaluate structural integrity. Multirotor UAVs are able to reach many areas that humans and other robots cannot safely access. Because of their relatively short operational flight time compared to other robotic applications, using multiple UAVs to collaboratively map these environments can streamline the mapping process significantly. This research focuses on four primary areas regarding autonomous mapping and navigation with multiple UAVs in complex unknown or partially unknown GPS-denied environments: The first area is …
Navigation Constellation Design Using A Multi-Objective Genetic Algorithm, Heather C. Diniz
Navigation Constellation Design Using A Multi-Objective Genetic Algorithm, Heather C. Diniz
Theses and Dissertations
In satellite constellation design, performance and cost of the system drive the design process. The Global Positioning System (GPS) constellation is currently used to provide positioning and timing worldwide. As satellite technology has improved over the years, the cost to develop and maintain the satellites has increased. Using a constellation design tool, it is possible to analyze the tradeoffs of new navigation constellation designs (Pareto fronts) that illustrate the tradeoffs between position dilution of precision (PDOP) and system cost. This thesis utilized Satellite Tool Kit (STK) to calculate PDOP values of navigation constellations, and the Unmanned Spacecraft Cost Model (USCM) …
Structural Analysis And Optimization Of Skyscrapers Connected With Skybridges And Atria, Amy Jean Taylor Mccall
Structural Analysis And Optimization Of Skyscrapers Connected With Skybridges And Atria, Amy Jean Taylor Mccall
Theses and Dissertations
Skybridges and atria between buildings are becoming more and more popular. Most current skybridge connections are either roller or rigid-connections. This dissertation presents an investigation of the structural analysis and optimization of skyscraper systems with hinge-connected skybridges, and compares the results to skyscraper systems with roller-connected skybridges and to skyscraper systems without skybridges altogether. Also presented is an investigation of the structural analysis and optimization of skyscrapers both with and without atria between the buildings. It was assumed that the atria envelope was constructed with cushions made from lightweight, transparent, and flexible Ethylene Tetrafluoroethylene (ETFE). A simplified skyscraper skybridge model …
Computational Design Optimization Of Arc Welding Process For Reduced Distortion In Welded Structures, Mohammad Refatul Islam
Computational Design Optimization Of Arc Welding Process For Reduced Distortion In Welded Structures, Mohammad Refatul Islam
Theses and Dissertations
An effective approach to determine optimum welding process parameters is implementation of advanced computer aided engineering (CAE) tool that integrates efficient optimization techniques and numerical welding simulation. In this thesis, an automated computational methodology to determine optimum arc welding process parameters is proposed. It is a coupled Genetic Algorithms (GA) and Finite Element (FE) based optimization method where GA directly utilizes output responses of FE based welding simulations for iterative optimization. Effectiveness of the method has been demonstrated by predicting optimum parameters of a lap joint specimen of two thin steel plates and automotive structure of nonlinear welding path for …
Bit-Error-Rate-Minimizing Channel Shortening Using Post-Feq Diversity Combining And A Genetic Algorithm, Gokhan Altin
Bit-Error-Rate-Minimizing Channel Shortening Using Post-Feq Diversity Combining And A Genetic Algorithm, Gokhan Altin
Theses and Dissertations
In advanced wireline or wireless communication systems, i.e., DSL, IEEE 802.11a/g, HIPERLAN/2, etc., a cyclic prefix which is proportional to the channel impulse response is needed to append a multicarrier modulation (MCM) frame for operating the MCM accurately. This prefix is used to combat inter symbol interference (ISI). In some cases, the channel impulse response can be longer than the cyclic prefix (CP). One of the most useful techniques to mitigate this problem is reuse of a Channel Shortening Equalizer (CSE) as a linear preprocessor before the MCM receiver in order to shorten the effective channel length. Channel shortening filter …
Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Application Of Optimization Techniques To Spectrally Modulated, Spectrally Encoded Waveform Design, Todd W. Beard
Theses and Dissertations
A design process is demonstrated for a coexistent scenario containing Spectrally Modulated, Spectrally Encoded (SMSE) and Direct Sequence Spread Spectrum (DSSS) signals. Coexistent SMSE-DSSS designs are addressed under both perfect and imperfect DSSS code tracking conditions using a non-coherent delay-lock loop (DLL). Under both conditions, the number of SMSE subcarriers and subcarrier spacing are the optimization variables of interest. For perfect DLL code tracking conditions, the GA and RSM optimization processes are considered independently with the objective function being end-to-end DSSS bit error rate. A hybrid GA-RSM optimization process is used under more realistic imperfect DLL code tracking conditions. In …
Improvement Of Ecm Techniques Through Implementation Of A Genetic Algorithm, James D. Townsend
Improvement Of Ecm Techniques Through Implementation Of A Genetic Algorithm, James D. Townsend
Theses and Dissertations
This research effective effort develops the necessary interfaces between the radar signal processing components and an optimization routine, such as genetic algorithms, to develop Electronic Countermeasure (ECM) waveforms under a Hardware-in-the-Loop (HILS) architecture. The various ECM waveforms are stored in an ECM library, where an operator selects the desired function to use against a particular system. This optimization works with modular components, compared to previous research that embedded a genetic algorithm into the Range Gate Pull-off (RGPO) waveform optimization loop, which can be interchanged based upon the operator's desired hardware/ software testing setup. The ECM library's first entries contain the …
Exploitation Of Self Organization In Uav Swarms For Optimization In Combat Environments, Dustin J. Nowak
Exploitation Of Self Organization In Uav Swarms For Optimization In Combat Environments, Dustin J. Nowak
Theses and Dissertations
This investigation focuses primarily on the development of effective target engagement for unmanned aerial vehicle (UAV) swarms using autonomous self-organized cooperative control. This development required the design of a new abstract UAV swarm control model which flows from an abstract Markov structure, a Partially Observable Markov Decision Process. Self-organization features, bio-inspired attack concepts, evolutionary computation (multi-objective genetic algorithms, differential evolution), and feedback from environmental awareness are instantiated within this model. The associated decomposition technique focuses on the iterative deconstruction of the problem domain state and dynamically building-up of self organizational rules as related to the problem domain environment. Resulting emergent …
The Vehicle Routing Problem With Simultaneous Pick-Up And Deliveries And A Grasp-Ga Based Solution Heuristic, Arif Volkan Vural
The Vehicle Routing Problem With Simultaneous Pick-Up And Deliveries And A Grasp-Ga Based Solution Heuristic, Arif Volkan Vural
Theses and Dissertations
In this dissertation, the vehicle routing problem and one of its variants, the vehicle routing problem with simultaneous pick up and deliveries (VRPSPD) are studied. The traditional vehicle routing problem (VRP) consists of constructing minimum cost routes for the vehicles to follow so that the set of customers are visited only once. A lot of effort has been devoted to research on developing fast and effective solution methods for many different versions of this problem by different majors of engineering profession. Thus, a structuring effort is needed to organize and document the vast literature so far has accumulated in this …
A Study Of Genetic Representation Schemes For Scheduling Soft Real-Time Systems, Amit Bugde
A Study Of Genetic Representation Schemes For Scheduling Soft Real-Time Systems, Amit Bugde
Theses and Dissertations
This research presents a hybrid algorithm that combines List Scheduling (LS) with a Genetic Algorithm (GA) for constructing non-preemptive schedules for soft real-time parallel applications represented as directed acyclic graphs (DAGs). The execution time requirements of the applications' tasks are assumed to be stochastic and are represented as probability distribution functions. The performance in terms of schedule lengths for three different genetic representation schemes are evaluated and compared for a number of different DAGs. The approaches presented in this research produce shorter schedules than HLFET, a popular LS approach for all of the sample problems. Of the three genetic representation …
A Platform For Antenna Optimization With Numerical Electromagnetics Code Incorporated With Genetic Algorithms, Timothy L. Pitzer
A Platform For Antenna Optimization With Numerical Electromagnetics Code Incorporated With Genetic Algorithms, Timothy L. Pitzer
Theses and Dissertations
This thesis investigation presents a unique incorporation of the Method of Moments (MoM) with a Genetic Algorithm (GA). A GA is used in accord with the Numerical Electromagnetics Code, Version 4 (NEC4) to create and optimize typical wire antenna designs, including single elements and arrays. Design parameters for the antenna are defined and encoded into a chromosome composed of a series of numbers. The cost function associated with the specific antenna of interest is what quantifies improvement and, eventually, optimization. This cost function is created and used by the GA to evaluate the performance of a population of antenna designs. …
Explicit Building Block Multiobjective Evolutionary Computation: Methods And Applications, Richard O. Day
Explicit Building Block Multiobjective Evolutionary Computation: Methods And Applications, Richard O. Day
Theses and Dissertations
This dissertation presents principles, techniques, and performance of evolutionary computation optimization methods. Concentration is on concepts, design formulation, and prescription for multiobjective problem solving and explicit building block (BB) multiobjective evolutionary algorithms (MOEAs). Current state-of-the-art explicit BB MOEAs are addressed in the innovative design, execution, and testing of a new multiobjective explicit BB MOEA. Evolutionary computation concepts examined are algorithm convergence, population diversity and sizing, genotype and phenotype partitioning, archiving, BB concepts, parallel evolutionary algorithm (EA) models, robustness, visualization of evolutionary process, and performance in terms of effectiveness and efficiency. The main result of this research is the development of …
Weapon Release Scheduling From Multiple-Bay Aircraft Using Multi-Objective Evolutionary Algorithms, Francis R. Lyons Iv
Weapon Release Scheduling From Multiple-Bay Aircraft Using Multi-Objective Evolutionary Algorithms, Francis R. Lyons Iv
Theses and Dissertations
The United States Air Force has put an increased emphasis on the timely delivery of precision weapons. Part of this effort has been to us multiple bay aircraft such the B-1B Lancer and B-52 Stratofortress to provide Close Air Support and responsive strikes using 1760 weapons. In order to provide greater flexibility, the aircraft carry heterogeneous payloads which can require deconfliction in order to drop multiple different types of weapons. Current methods of deconfliction and weapon selection are highly crew dependent and work intensive. This research effort investigates the optimization of an algorithm for weapon release which allows the aircraft …
A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell
A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell
Theses and Dissertations
This research investigation addresses the problem of routing and simulating swarms of UAVs. Sorties are modeled as instantiations of the NP-Complete Vehicle Routing Problem, and this work uses genetic algorithms (GAs) to provide a fast and robust algorithm for a priori and dynamic routing applications. Swarms of UAVs are modeled based on extensions of Reynolds' swarm research and are simulated on a Beowulf cluster as a parallel computing application using the Synchronous Environment for Emulation and Discrete Event Simulation (SPEEDES). In a test suite, standard measures such as benchmark problems, best published results, and parallel metrics are used as performance …
Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, And Developing, Jesse B. Zydallis
Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, And Developing, Jesse B. Zydallis
Theses and Dissertations
This dissertation research emphasizes explicit Building Block (BB) based MO EAs performance and detailed symbolic representation. An explicit BB-based MOEA for solving constrained and real-world MOPs is developed the Multiobjective Messy Genetic Algorithm II (MOMGA-II) which is designed to validate symbolic BB concepts. The MOMGA-II demonstrates that explicit BB-based MOEAs provide insight into solving difficult MOPs that is generally not realized through the use of implicit BB-based MOEA approaches. This insight is necessary to increase the effectiveness of all MOEA approaches. In order to increase MOEA computational efficiency parallelization of MOEAs is addressed. Communications between processors in a parallel MOEA …
A Multiobjective Approach Applied To The Protein Structure Prediction Problem, Richard O. Day
A Multiobjective Approach Applied To The Protein Structure Prediction Problem, Richard O. Day
Theses and Dissertations
Interest in discovering a methodology for solving the Protein Structure Prediction problem extends into many fields of study including biochemistry, medicine, biology, and numerous engineering and science disciplines. Experimental approaches, such as, x-ray crystallographic studies or solution Nuclear Magnetic Resonance Spectroscopy, to mathematical modeling, such as minimum energy models are used to solve this problem. Recently, Evolutionary Algorithm studies at the Air Force Institute of Technology include the following: Simple Genetic Algorithm (GA), messy GA, fast messy GA, and Linkage Learning GA, as approaches for potential protein energy minimization. Prepackaged software like GENOCOP, GENESIS, and mGA are in use to …
Data Mining Feature Subset Weighting And Selection Using Genetic Algorithms, Okan Yilmaz
Data Mining Feature Subset Weighting And Selection Using Genetic Algorithms, Okan Yilmaz
Theses and Dissertations
We present a simple genetic algorithm (sGA), which is developed under Genetic Rule and Classifier Construction Environment (GRaCCE) to solve feature subset selection and weighting problem to have better classification accuracy on k-nearest neighborhood (KNN) algorithm. Our hypotheses are that weighting the features will affect the performance of the KNN algorithm and will cause better classification accuracy rate than that of binary classification. The weighted-sGA algorithm uses real-value chromosomes to find the weights for features and binary-sGA uses integer-value chromosomes to select the subset of features from original feature set. A Repair algorithm is developed for weighted-sGA algorithm to guarantee …
Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest
Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest
Theses and Dissertations
The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return to a safe destination (usually the starting point). The process of selecting such a flight path is known as the Mission Route Planning (MRP) Problem and is a three-dimensional, multi-criteria (fuel expenditure, time required, risk taken, priority targeting, goals met, etc.) path search. Planning aircraft routes involves an elaborate search through numerous possibilities, which can severely task the resources of the system being used to compute the routes. Operational systems can take up to a day to arrive at a solution due …
Implementation And Analysis Of The Parallel Genetic Rule And Classifier Construction Environment, David M. Strong
Implementation And Analysis Of The Parallel Genetic Rule And Classifier Construction Environment, David M. Strong
Theses and Dissertations
This paper discusses the Genetic Rule and Classifier Construction Environment (GRaCCE), which is an alternative to existing decision rule induction (DRI) algorithms. GRaCCE is a multi-phase algorithm which uses evolutionary search to mine classification rules from data. The current implementation uses a genetic algorithm based 0/1 search to reduce the number of features to a minimal set of features that make the most significant contributions to the classification of the input data set. This feature selection increases the efficiency of the rule induction algorithm that follows. However, feature selection is shown to account for more than 98 percent of the …
Use Of Genetic Algorithms To Characterize Groundwater Contamination Source Areas, Chaz M. Williamson
Use Of Genetic Algorithms To Characterize Groundwater Contamination Source Areas, Chaz M. Williamson
Theses and Dissertations
In this work, genetic algorithms (GAs) were used to help interpret tracer breakthrough curves from partitioning interwell tracer tests (PITTs) conducted at Hill AFB, Utah by researchers from the University of Florida. Two transport models were developed to simulate tracer transport in the test cells. One model assumed the cell consisted of multiple layers, and that transport in each layer could he described by the one-dimensional advective/dispersive equation. The second model also assumed multiple layers, and modeled transport in the individual layers as advective transport through 100 tubes. Transport times were represented by a stochastic (lognormal) distribution. The model solutions …
A Comparison Of Genetic Algorithm Parametrization On Synthetic Optimization Problems, Mehmet Eravsar
A Comparison Of Genetic Algorithm Parametrization On Synthetic Optimization Problems, Mehmet Eravsar
Theses and Dissertations
Meta-heuristics have been deployed to solve many hard combinatorial and optimization problems. Parameterization of meta-heuristics is an important challenging aspect of meta-heuristic use since many of the features of these algorithms cannot be explained theoretically. Experiences with Genetic Algorithms (GA) applied to Multidimensional Knapsack Problems (MKP) have shown that this class of algorithm is very sensitive to parameterization. Many studies use standard test problems, which provide a firm basis for study comparisons but ignore the effect of problem correlation structure. This thesis applies GA to MKP. A new random repair operator, which projects infeasible solutions into feasible region, is proposed. …
Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms, Karl R. Deerman
Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms, Karl R. Deerman
Theses and Dissertations
AFIT has had a long-standing interest in solving the protein structure prediction (PSP) problem. The PSP problem is an intractable problem that if "solved" can lead to revolutionary new techniques for everything from the development of new medicines to optical computer switches. The challenge is to find a reliable and consistent method of predicting the 3-dimensional structure of a protein given its defining sequence of amino acids. PSP is primarily concerned with predicting the tertiary protein structure without regards to how the protein came to this folded state. The tertiary structure determines the protein's functionality.
Refined Genetic Algorithms For Polypeptide Structure Prediction, Charles E. Kaiser Jr.
Refined Genetic Algorithms For Polypeptide Structure Prediction, Charles E. Kaiser Jr.
Theses and Dissertations
Accurate and reliable prediction of macromolecular structures has eluded researchers for nearly 40 years. Prediction via energy minimization assumes the native conformation has the globally minimal energy potential. An exhaustive search is impossible since for molecules of normal size, the size of the search space exceeds the size of the universe. Domain knowledge sources, such as the Brookhaven PDB can be mined for constraints to limit the search space. Genetic algorithms (GAs) are stochastic, population based, search algorithms of polynomial (P) time complexity that can produce semi-optimal solutions for problems of nondeterministic polynomial (NP) time complexity such as PSP. Three …
Analysis Of Linkage-Friendly Genetic Algorithms, Laurence D. Merkle
Analysis Of Linkage-Friendly Genetic Algorithms, Laurence D. Merkle
Theses and Dissertations
Evolutionary algorithms (EAs) are stochastic population-based algorithms inspired by the natural processes of selection, mutation, and recombination. EAs are often employed as optimum seeking techniques. A formal framework for EAs is proposed, in which evolutionary operators are viewed as mappings from parameter spaces to spaces of random functions. Formal definitions within this framework capture the distinguishing characteristics of the classes of recombination, mutation, and selection operators. EAs which use strictly invariant selection operators and order invariant representation schemes comprise the class of linkage-friendly genetic algorithms (lfGAs). Fast messy genetic algorithms (fmGAs) are lfGAs which use binary tournament selection (BTS) with …
Clustered Microcalcification Detection Using Optimized Difference Of Gaussians, Edward M. Ochoa
Clustered Microcalcification Detection Using Optimized Difference Of Gaussians, Edward M. Ochoa
Theses and Dissertations
The objective of this thesis is to design an automated microcalcification detection system to be used as an aid in radiologic mammogram interpretation. This research proposes the following methodology for clustered microcalcification detection. First, preprocess the digitized film mammogram to reduce digitization noise. Second, spatially filter the image with a difference of Gaussians (DoG) kernel. To detect potential microcalcifications, segment the filtered image using global and local thresholding. Next, cluster and index these detections into regions of interest (ROIs). Identify ROIs on the digitized image (or hardcopy printout) for final radiologic diagnosis.
The Application Of Hybridized Genetic Algorithms To The Protein Folding Problem, Robert L. Gaulke
The Application Of Hybridized Genetic Algorithms To The Protein Folding Problem, Robert L. Gaulke
Theses and Dissertations
The protein folding problem consists of attempting to determine the native conformation of a protein given its primary structure. This study examines various methods of hybridizing a genetic algorithm implementation in order to minimize an energy function and predict the conformation (structure) of Met-enkephalin. Genetic Algorithms are semi-optimal algorithms designed to explore and exploit a search space. The genetic algorithm uses selection, recombination, and mutation operators on populations of strings which represent possible solutions to the given problem. One step in solving the protein folding problem is the design of efficient energy minimization techniques. A conjugate gradient minimization technique is …
A Gain Scheduling Optimization Method Using Genetic Algorithms, Robert C. Martin Iv
A Gain Scheduling Optimization Method Using Genetic Algorithms, Robert C. Martin Iv
Theses and Dissertations
Gain scheduling. the traditional method of providing adaptive control to a nonlinear system, has long been an ad hoc design process. Until recently; little theoretical guidance directed this practitioners' art. For this reason a systematic study of this design process and its potential for optimization has never been accomplished. Additionally, the nonlinearities and the large search space involved in gain scheduling also precluded such an optimization study. Traditionally, the gain scheduling process has been some variation of a linear interpolation between discrete design points. By using powerful non-traditional optimization tools such as genetic algorithms there are ways of improving this …
Predicting Protein Structure Using Parallel Genetic Algorithms, George H. Gates Jr.
Predicting Protein Structure Using Parallel Genetic Algorithms, George H. Gates Jr.
Theses and Dissertations
The protein folding problem is a biochemistry Grand Challenge problem. The challenge is to reliably predict natural three-dimensional structures of polypeptides. Genetic algorithms (GAs) are robust, semi-optimal search techniques modeling natural evolutionary processes. Fast messy GAs (fmGAs) are variants of messy GAs that reduce the exponential time complexity to polynomial. This investigation evaluates the merits of parallel SGAs and fmGAs for minimizing the potential energy of a pentapeptide, (Met)-enkephalin. AFIT's energy model is compared to a similar model in a commercial package called QUANTA. Differences between the two models are identified and resolved to enhance GAs' abilities to correctly fold …