Dissertations / Theses on the topic 'Evolutionary programming (computer science)'
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Tati, Kiran Kumar Smilkstein Tina Harriet. "General purpose evolutionary algorithm testbed." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/5359.
Full textJob, Dominic Edward. "Case-based reasoning and evolutionary computation techniques for FPGA programming." Thesis, Edinburgh Napier University, 2001. http://researchrepository.napier.ac.uk/Output/4272.
Full textDavis, Edward V. "Software testing for evolutionary iterative rapid prototyping." Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA232555.
Full textThesis Advisor(s): Shimeall, Timothy J. Second Reader: Barnes, Patrick D. "December 1990." Description based on title screen as viewed on March 29, 2010. DTIC Identifier(s): Computer Program Verification, Prototypes, Software Engineering, User Manuals. Author(s) subject terms: Software Testing, Software Prototyping, Rapid Prototyping, Reusable Components, Requirements-based Testing, Software Testing Tools. Includes bibliographical references (p. 276-281). Also available in print.
Heinze, Glenn. "Application of evolutionary algorithm strategies to entity relationship diagrams /." View PDF document on the Internet, 2004. http://library.athabascau.ca/scisthesis/Heinze.pdf.
Full textSchwartz, Bonnie Jo. "An Evolutionary Programming Algorithm for Automatic Chromatogram Alignment." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1175715183.
Full textWilkerson, Joshua Lee. "Co-evolutionary automated software correction: a proof of concept." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2008. http://scholarsmine.mst.edu/thesis/pdf/Wilkerson_09007dcc80642bb4.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed June 18, 2009) Includes bibliographical references (p. 62-64).
Gramz, James. "Using Evolutionary Programming to increase the accuracy of an ensemble model for energy forecasting." Thesis, Marquette University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1554240.
Full textNatural gas companies are always trying to increase the accuracy of their forecasts. We introduce evolutionary programming as an approach to forecast natural gas demand more accurately. The created Evolutionary Programming Engine and Evolutionary Programming Ensemble Model use the current GasDay models, along with weather and historical flow to create an overall forecast for the amount of natural gas a company will need to supply to their customers on a given day. The existing ensemble model uses the GasDay component models and then tunes their individual forecasts and combines them to create an overall forecast.
The inputs into the Evolutionary Programming Engine and Evolutionary Programming Ensemble Model were determined based on currently used inputs and domain knowledge about what variables are important for natural gas forecasting. The ensemble model design is based on if-statements that allow different equations to be used on different days to create a more accurate forecast, given the expected weather conditions.
This approach is compared to what GasDay currently uses based on a series of error metrics and comparisons on different types of weather days and during different months. Three different operating areas are evaluated, and the results show that the created Evolutionary Programming Ensemble Model is capable of creating improved forecasts compared to the existing ensemble model, as measured by Root Mean Square Error (RMSE) and Standard Error (Std Error). However, the if-statements in the ensemble models were not able to produce individually reasonable forecasts, which could potentially cause errant forecasts if a different set of if-statements are true on a given day.
Hong, Libin. "Hyper-heuristic approaches to automatically designing heuristics as mutation operators for evolutionary programming on function classes." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52348/.
Full textNwamba, André Chidi. "Automated offspring sizing in evolutionary algorithms." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2009. http://scholarsmine.mst.edu/thesis/pdf/Nwamba_09007dcc8068c83d.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed August 10, 2009) Includes bibliographical references (p. 49-51).
Skolicki, Zbigniew Maciej. "An analysis of island models in evolutionary computation." Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2954.
Full textTitle from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Kenneth A. De Jong. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Vita: p. 422. Includes bibliographical references (p. 413-421). Also available in print.
Petrovic, Pavel. "Incremental Evolutionary Methods for Automatic Programming of Robot Controllers." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1748.
Full textThe aim of the main work in the thesis is to investigate Incremental Evolution methods for designing a suitable behavior arbitration mechanism for behavior-based (BB) robot controllers for autonomous mobile robots performing tasks of higher complexity. The challenge of designing effective controllers for autonomous mobile robots has been intensely studied for few decades. Control Theory studies the fundamental control principles of robotic systems. However, the technological progress allows, and the needs of advanced manufacturing, service, entertainment, educational, and mission tasks require features beyond the scope of the standard functionality and basic control. Artificial Intelligence has traditionally looked upon the problem of designing robotics systems from the high-level and top-down perspective: given a working robotic device, how can it be equipped with an intelligent controller. Later approaches advocated for better robustness, modifiability, and control due to a bottom-up layered incremental controller and robot building (Behavior-Based Robotics, BBR). Still, the complexity of programming such system often requires manual work of engineers. Automatic methods might lead to systems that perform task on demand without the need of expert robot programmer. In addition, a robot programmer cannot predict all the possible situations in the robotic applications. Automatic programming methods may provide flexibility and adaptability of the robotic products with respect to the task performed. One possible approach to automatic design of robot controllers is Evolutionary Robotics (ER). Most of the experiments performed in the field of ER have achieved successful learning of target task, while the tasks were of limited complexity. This work is a marriage of incremental idea from the BBR and automatic programming of controllers using ER. Incremental Evolution allows automatic programming of robots for more complex tasks by providing a gentle and easy-to understand support by expertknowledge — division of the target task into sub-tasks. We analyze different types of incrementality, devise new controller architecture, implement an original simulator compatible with hardware, and test it with various incremental evolution tasks for real robots. We build up our experimental field through studies of experimental and educational robotics systems, evolutionary design, distributed computation that provides the required processing power, and robotics applications. University research is tightly coupled with education. Combining the robotics research with educational applications is both a useful consequence as well as a way of satisfying the necessary condition of the need of underlying application domain where the research work can both reflect and base itself.
Wong, King Hei. "Solving combinatorial based chemical engineering problems via parallel evolutionary approaches /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?CBME%202010%20WONGK.
Full textService, Travis. "Co-optimization: a generalization of coevolution." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2008. http://scholarsmine.mst.edu/thesis/pdf/Service_09007dcc804e2264.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed April 26, 2008) Includes bibliographical references (p. 65-68).
Olivier, Hannes Friedel. "The expected runtime of the (1+1) evolutionary algorithm on almost linear functions." Virtual Press, 2006. http://liblink.bsu.edu/uhtbin/catkey/1356253.
Full textDepartment of Computer Science
Thai, Cau Doan Hoang Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "A new evolutionary optimisation method for the operation of power systems with multiple storage resources." Awarded by:University of New South Wales. School of Electrical Engineering & Telecommunications, 2000. http://handle.unsw.edu.au/1959.4/17603.
Full textDick, Grant, and n/a. "Spatially-structured niching methods for evolutionary algorithms." University of Otago. Department of Information Science, 2008. http://adt.otago.ac.nz./public/adt-NZDU20080902.161336.
Full textOaken, David R. "Optimisation of definition structures & parameter values in process algebra models using evolutionary computation." Thesis, University of Stirling, 2014. http://hdl.handle.net/1893/21206.
Full textWong, Yin-cheung Eugene, and 黃彥璋. "A hybrid evolutionary algorithm for optimization of maritime logisticsoperations." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44526763.
Full textVulli, Srinivasa Shivakar. "An artificial life approach to evolutionary computation: from mobile cellular algorithms to artificial ecosystems." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2010. http://scholarsmine.mst.edu/thesis/pdf/Vulli_09007dcc807d69aa.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed July 19, 2010) Includes bibliographical references (p. 57-60).
Fu, Ser-Geon. "Genetic and evolutionary protocols for solving distributed asymmetric constraint satisfaction problems." Auburn, Ala., 2007. http://repo.lib.auburn.edu/2007%20Spring%20Dissertations/FU_SER-GEON_10.pdf.
Full textMurdock, J. William. "Self-improvment through self-understanding : model-based reflection for agent adaptation." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/8225.
Full textGadiraju, Sriphani Raju. "Modified selection mechanisms designed to help evolution strategies cope with noisy response surfaces." Master's thesis, Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-07022003-164112.
Full textJohansson, Ulf. "Obtaining Accurate and Comprehensible Data Mining Models : An Evolutionary Approach." Doctoral thesis, Linköping : Department of Computer and Information Science, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8881.
Full textKishore, Krishna J. "Genetic Programming Based Multicategory Pattern Classification." Thesis, Indian Institute of Science, 2001. https://etd.iisc.ac.in/handle/2005/75.
Full textKishore, Krishna J. "Genetic Programming Based Multicategory Pattern Classification." Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/75.
Full textHoang, Tuan-Hoa Information Technology & Electrical Engineering Australian Defence Force Academy UNSW. "Evolutionary Developmental Evaluation : the Interplay between Evolution and Development." Awarded by:University of New South Wales - Australian Defence Force Academy. Information Technology & Electrical Engineering, 2009. http://handle.unsw.edu.au/1959.4/44870.
Full textHoff, Carl C. "Pattern Recognition via Machine Learning with Genetic Decision-Programming." Wright State University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=wright1133882117.
Full textWeninger, Timothy Edwards. "Link discovery in very large graphs by constructive induction using genetic programming." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1087.
Full textSmart, Otis Lkuwamy. "Evolutionary algorithms and frequent itemset mining for analyzing epileptic oscillations." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/22709.
Full textCommittee Chair: Vachtsevanos, George J.; Committee Co-Chair: Litt, Brian; Committee Member: Butera, Robert J.; Committee Member: Echauz, Javier; Committee Member: Howard, Ayanna M.; Committee Member: Williams, Douglas B.
Muthuswamy, Shanthi. "Discrete particle swarm optimization algorithms for orienteering and team orienteering problems." Diss., Online access via UMI:, 2009.
Find full textGarret, Aaron Dozier Gerry V. "Neural enhancement for multiobjective optimization." Auburn, Ala., 2008. http://repo.lib.auburn.edu/EtdRoot/2008/SPRING/Computer_Science_and_Software_Engineering/Dissertation/Garrett_Aaron_55.pdf.
Full textDi, Pietro Anthony. "Optimising evolutionary strategies for problems with varying noise strength." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0210.
Full textKhan, Salman A. "Design and analysis of evolutionary and swarm intelligence techniques for topology design of distributed local area networks." Pretori: [S.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-09272009-153908/.
Full textMeuth, Ryan James. "Meta-learning computational intelligence architectures." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2009. http://scholarsmine.mst.edu/thesis/pdf/Meuth_09007dcc80722172.pdf.
Full textVita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed January 5, 2010) Includes bibliographical references (p. 152-159).
Allgaier, Nicholas. "Reverse Engineering the Human Brain: An Evolutionary Computation Approach to the Analysis of fMRI." ScholarWorks @ UVM, 2015. http://scholarworks.uvm.edu/graddis/383.
Full textChopra, Shubham. "Evolved Design of a Nonlinear Proportional Integral Derivative (NPID) Controller." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/512.
Full textNguyen, Thuy-Linh 1964. "An object-oriented data model for evolvable Web systems." Monash University, School of Computer Science and Software Engineering, 2000. http://arrow.monash.edu.au/hdl/1959.1/9008.
Full textKalegari, Diego Humberto. "Algoritmo de evolução diferencial paralelo aplicado ao problema da predição da estrutura de proteínas utilizando o modelo AB em 2D e 3D." Universidade Tecnológica Federal do Paraná, 2010. http://repositorio.utfpr.edu.br/jspui/handle/1/1043.
Full textProtein structure prediction is a well-known problem in bioinformactis. Identifying protein native conformation makes it possible to predict its function within the organism. Knowing this also helps in the development of new medicines and in comprehending how some illnesses work and act. During the past year some techniques have been proposed to solve this problem, but its high cost made it necessary to build models that simplify the protein structures. However, even with the simplicity of these models identifying the protein native conformation remains a highly complex, computationally challenging problem. This paper uses an evolutionary algorithm known as Differential Evolution (DE) to solve the protein structure prediction problem. The model used to represent the protein structure is the Toy Model (also known as the AB Model) in both 2D and 3D. This work implements two versions of the ED algorithm using a parallel architecture (master-slave) based on Message Passing interface in a cluster. A large number of tests were executed to define the final configuration of the DE operators for both models. A new set of special operators were developed: explosion and mirror mutation. We can consider the first as generic, because it can be used in any problem. The second one is more specific because it requires previous knowledge of the problem. Of the two DE algorithm implemented, one is a basic DE algorithm and the second is a self-adaptive DE. All tests executed in this work used four benchmark amino acid sequences generated from the Fibonacci sequence. Each sequence has 13 to 55 amino acids. The results for both parallel DE algorithms using both 2D and 3D models were compared with other works. The DE algorithm achieved excellent results. It did not achieve the optimal known values for some sequences, but it was competitive with other specialized methods. Overall results encourage further research toward the use of knowledge-based operators and biologically inspired techniques to improve DE algorithm performance.
Mambrini, Andrea. "Theory grounded design of genetic programming and parallel evolutionary algorithms." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5928/.
Full textJohnson, Colin G. "A design framework for evolutionary algorithms." Thesis, University of Kent, 2003. https://kar.kent.ac.uk/13944/.
Full textLycett, Mark Geoffrey. "The development of component-based evolutionary information systems." Thesis, Brunel University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266634.
Full textJaber, Ahmed. "Hybrid Algorithm for Multi-objective Mixed-integer Non-convex Mechanical Design Optimization Problems." Thesis, Troyes, 2021. http://www.theses.fr/2021TROY0034.
Full textMulti-objective mixed-integer non-convex non-linear constrained optimization problems that appears in several fields especially in mechanical applications. This thesis aims to develop a new method to solve such problems. Our proposal is a hybridization of the Multi-Criteria Branch-and-Bound (MCBB) algorithm with the Non-dominated Sorting Genetic Algorithm 2 (NSGAII). The proposed approach is furthermore enhanced by new branching strategies designed for MCBB. The constraints are handled using a new proposed constraint handling technique for evolutionary algorithms. Numerical experiments based on statistical assessment are done in this thesis to examine the performance of the new proposed approach. Results show the competitive performance of our algorithm among NSGAII. We propose two applications of our proposed approach: "Search Feasibility" and "Seek Optimality" applications. Both are applied on a real-world state of art 3 stages reducer problem which is formulated in this thesis to a bi-objective problem to meet the requirement of ISO standards on calculation of load capacity of gears
Iyer, Swami. "Evolutionary dynamics on complex networks." Thesis, University of Massachusetts Boston, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3564666.
Full textMany complex systems such as the Internet can be represented as networks, with vertices denoting the constituent components of the systems and edges denoting the patterns of interactions among the components. In this thesis, we are interested in how the structural properties of a network, such as its average degree, degree distribution, clustering, and homophily affect the processes that take place on it. In the first part of the thesis we focus on evolutionary game theory models for studying the evolution of cooperation in a population of predominantly selfish individuals. In the second part we turn our attention to an evolutionary model of disease dynamics and the impact of vaccination on the spread of infection. Throughout the thesis we use a network as an abstraction for a population, with vertices representing individuals in the population and edges specifying who can interact with whom. We analyze our models for a well-mixed population, i.e., an infinite population with random mixing, and compare the theoretical results with those obtained from computer simulations on model and empirical networks.
Wu, James 1975. "A comparison of programming languages for real-time, safety-critical programming /." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=30772.
Full textThis paper explores the language characteristics that can impact the safety and reliability of the software produced. The goal is to provide a set of criteria that can be used for the selection of an appropriate language for real-time, safety-critical development. It proposes a set of characteristics that can affect the suitability of a language to such development, and compares a selection of common programming languages, including Ada, C, C++ and Java, against this framework.
May, Peter S. "Test data generation : two evolutionary approaches to mutation testing." Thesis, University of Kent, 2007. https://kar.kent.ac.uk/24023/.
Full textHolly, Matthew James. "An evolutionary computation framework for microarchitecture design /." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=78379.
Full textThis study presents a software framework for designing microarchitecture. As a case study, a genetic algorithm is used to automatically synthesize two-level indirect branch predictors. The evolved designs routinely deliver enhanced performance as compared to the equivalent, highly optimized structures created by hand. The primary drawback associated with this method is the excessive design complexity induced by unconstrained evolution. Several methods of incorporating simplicity of design into the evolutionary process are investigated. A unified fitness metric, combining both simplicity and performance, leads to the evolution of simple and effective designs.
Williams, Bryn V. "Evolutionary neural networks : models and applications." Thesis, Aston University, 1995. http://publications.aston.ac.uk/10635/.
Full textGamble, James Graham. "Explicit parallel programming." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-06082009-171019/.
Full textPalmieri, David Walsh. "Knowledge Management Through Pair Programming." NCSU, 2002. http://www.lib.ncsu.edu/theses/available/etd-20020328-093026.
Full textKnowledge Management has been the subject of increasing focus over the last several years. Literature and research on the topic has grown as companies and organizations have come to realize that success is often determined by one's ability to create, disseminate, and embody knowledge in products and services. This realization has led to increased interest in examining the ways in which knowledge can be effectively created, identified, codified, disseminated, and retained. The field of Knowledge Management has emerged to address this need.
One of the obstacles that Knowledge Management seeks to overcome is the natural tendency in people to hoard knowledge. People often withhold knowledge when they feel it provides them with a competitive advantage over others. Many traditional management incentives and team structures create and perpetuate competitive environments that encourage knowledge hoarding. Knowledge Management also seeks to find ways to reduce the impact of employee turnover. When an employee leaves a company or organization, the knowledge they possess often goes with them. This loss can potentially have a negative impact on the productivity and quality of the company or organization. Knowledge Management seeks to find ways to minimize loss of knowledge when an employee leaves a company or organization.
Pair programming is a practice that holds promise for overcoming some of the challenges faced by Knowledge Management. In pair programming, two programmers work side-by-side at one computer collaborating on the same design, algorithm, code, or test. The continual interaction between pair programmers would seem to provide an environment that promotes knowledge sharing, and collaborative knowledge discovery. Additionally, through pair rotation, in which pairs change partners fairly often, tacit knowledge might be spread more effectively through face-to-face communication than by documentation, databases, or other means.
This research examines pair programming in the realm of Knowledge Management, positing the following hypotheses:Pair programming reduces the tendency of people to hoard knowledge.Pair programming reduces the impact of employee turnover.Pair programming is an effective means of knowledge dissemination and knowledge retention that has a positive influence on the Knowledge Management practices of a company or organization.
These hypotheses are tested through the use of a survey of individuals in technology research, development, and service. Analysis of the survey results provided no conclusive evidence to either support or disprove the hypothesis that pair programming reduces the tendency of people to hoard knowledge. The results indicate support for the hypothesis that pair programming reduces the impact of employee turnover, although not statistically significant. And finally, the survey results indicate with statistical significance that pair programming is an effective means of knowledge dissemination and retention, with a positive influence on the Knowledge Management practices of a company or organization.
Wu, Cheng-Shiung Jesse. "A wysiwyg literate programming system /." The Ohio State University, 1990. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487683756125668.
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