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Dissertations / Theses on the topic 'Programming applications'
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1
Longley, Mark. "Functional programming applications." Thesis, University of Kent, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303191.
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Johnsson, Ola, Magnus Stenemo, and Zain-ul-Abdin. "Programming & Implementation of Streaming Applications." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-283.
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Streaming applications like multimedia and radar signal processing applications are becoming increasingly compute-intensive. To overcome the computational demands new parallel architectures are emerging. The programming tools provided with these architectures require low-level programming, which creates a need for a common high-level architecture independent language that can exploit parallelism efficiently. One such language is StreamIt, designed around the notions of streams and stream transformers, which allows efficient mapping to a variety of architectures. The overall goal of this master’s thesis is to evaluate the StreamIt language from a programmability and portability point of view. An MPD-application has been developed in StreamIt, which is executed on the RAW simulator. Furthermore, a code generator is designed to compile and execute the application on the XPP simulator. The conclusions drawn are that StreamIt is easy to learn, but hard to use because of its programming paradigm as compared to conventional languages. StreamIt programming involves thinking in terms of streams instead of globally accessed memory. The structure of StreamIt makes it easy to reuse components and modify the application. The construction of the compiler makes it possible to port StreamIt application to various architectures.
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Johnsson, Ola, Magnus Stenemo, and Zain ul-Abdin. "Programming & Implementation of Streaming Applications." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-283.
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Streaming applications like multimedia and radar signal processing applications are becoming
increasingly compute-intensive. To overcome the computational demands new parallel
architectures are emerging.
The programming tools provided with these architectures require low-level programming, which
creates a need for a common high-level architecture independent language that can exploit
parallelism efficiently. One such language is StreamIt, designed around the notions of streams
and stream transformers, which allows efficient mapping to a variety of architectures.
The overall goal of this master’s thesis is to evaluate the StreamIt language from a
programmability and portability point of view. An MPD-application has been developed in
StreamIt, which is executed on the RAW simulator. Furthermore, a code generator is designed to
compile and execute the application on the XPP simulator.
The conclusions drawn are that StreamIt is easy to learn, but hard to use because of its
programming paradigm as compared to conventional languages. StreamIt programming involves
thinking in terms of streams instead of globally accessed memory. The structure of StreamIt
makes it easy to reuse components and modify the application. The construction of the compiler
makes it possible to port StreamIt application to various architectures.
4
Davidescu, Diana Maria. "Convexifiable smooth programming and applications." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82216.
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This thesis is an introduction to the study of convexification problems involving smooth functions in the area of continuous mathematical programming. The results are applied to a real life problem in oil production. An improved model is formulated for the company which yields environmentally friendlier optimal solutions at the same profit level.
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Caroli, Alberto. "Genetic Programming applications in Robotics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amslaurea.unibo.it/5860/.
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Wang, Meng. "Bidirectional programming and its applications." Thesis, University of Oxford, 2011. http://kar.kent.ac.uk/55795/.
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Many problems in programming involve pairs of computations that cancel out each other's effects; some examples include parsing/printing, embed- ding/ projection, marshalling/unmarshalling, compressing/ de-com pressing etc. To avoid duplication of effort, the paradigm of bidirectional programming aims at to allow the programmer to write a single program that expresses both computations. Despite being a promising idea, existing studies mainly focus on the view-update problem in databases and its variants; and the impact of bidirectional programming has not reached the wider community. The goal of this thesis is to demonstrate, through concrete language designs and case studies, the relevance of bidirectional programming, in areas of computer science that have not been previously explored. In this thesis, we will argue for the importance of bidirectional programming in programming language design and compiler implementation. As evidence for this, we will propose a technique for incremental refactoring, which relies for its correctness on a bidirectional language and its properties, and devise a framework for implementing program transformations, with bidirectional properties that allow program analyses to be carried out in the transformed program, and have the results reported in the source program. Our applications of bidirectional programming to new areas bring up fresh challenges. This thesis also reflects on the challenges, and studies their impact to the design of bidirectional systems. We will review various design goals, including expressiveness, robustness, updatability, efficiency and easy of use, and show how certain choices, especially regarding updatability, can have significant influence on the effectiveness of bidirectional systems.
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Trujillo-Cortez, Refugio. "Stable convex parametric programming and applications." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=37856.
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This thesis is a study of stable perturbations in convex programming models. Stability of a general model is introduced as lower semicontinuity of the feasible set mapping. This stability is shown to be equivalent to the Robinson notion of stability and regularity. In the convex case, it is also equivalent to the full-rank Slater condition. Then, the relationships between various point-to-set mappings are studied for convex models and new implications between these mappings are established. Also, local and global optimality of parameters is studied. A new result here is a characterization of locally optimal parameters that does not require stable perturbations. This result is valid, in particular, for convex models with LFS constraints. The value of the model can be improved by one of several new formulations of the marginal value formula.The results on stability are applied for bilevel convex models and an algorithm for solving these models, based on a marginal value formula, is suggested and then applied to a real-life problem in the petroleum industry.
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Rochefort, Stephen. "Logic programming applications in educational environments." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0012/NQ61676.pdf.
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Costa, Alberto. "Applications of Reformulations in Mathematical Programming." Phd thesis, Ecole Polytechnique X, 2012. http://pastel.archives-ouvertes.fr/pastel-00746083.
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La programmation mathématique est une technique qui peut être utilisée pour résoudre des problèmes concrets où l'on veut maximiser, ou minimiser, une fonction objectif soumise à des contraintes sur les variables décisionnelles. Les caractéristiques les plus importantes de la programmation mathématique sont la création d'un modèle pour décrire le problème (aussi appelé formulation), et la mise en œuvre d'algorithmes efficaces pour le résoudre (aussi appelés solveurs). Dans cette thèse, on s'occupe du premier point. Plus précisemment, on étudie certains problèmes qui proviennent de domaines diffèrents, et en commençant par les modèles les plus naturels pour les décrire, on présente des formulations alternatives, qui partagent certaines propriétés avec le modèle original mais qui sont en quelque sorte meilleures (par exemple au niveau du temps d'exécution nécessaire pour obtenir la solution par le solveur). Ces nouveaux modèles sont appelés reformulations. On suit la classification des reformulations proposée par Liberti dans [Reformulations in Mathematical Programming: Definitions and Systematics, RAIRO-OR, 43(1):55-86, 2009]: exact reformulations (aussi appellées opt-reformulations), narrowings, relaxations. Cette thèse concerne trois applications de la programmation mathématique où les reformulations ont été fondamentales pour obtenir une bonne solution. Le premier problème étudié est le partitionnement de graphes sur la base de la maximisation de la modularité. Comme ce problème est NP-difficile, plusieurs heuristiques sont proposées. On s'occupe d'un algorithme séparatif hiérarchique qui fonctionne en divisant récursivement une classe en deux nouvelles classes de façon optimale. Cet étape de division est accomplie en résolvant un programme binaire quadratique et convexe. Il est reformulé de manière exacte pour obtenir une forme plus compacte sans modifier l'ensemble des solutions optimales (exact reformulation). On considère aussi l'impact donné par la réduction du nombre des solutions symétriques globalement optimales. Les temps d'exécution sont considérablement réduits par rapport à la formulation originelle. Le deuxième problème étudié dans cette thèse est le placement de cercles égaux dans un carré (Packing Equal Circles in a Square, ou PECS), où l'on veut placer des cercles égaux dans un carré de côté 1 sans avoir de superposition et en maximisant le rayon commun. L'une des raisons pour laquelle le problème est difficile à résoudre vient de la présence de plusieurs solutions symétriques optimales, et par conséquent un arbre de séparation-et-évaluation (ou Branch-and-Bound) très large. Certaines solutions symétriques optimales sont rendues irréalisables en ajoutant des contraintes pour briser les symétries (Symmetry Breaking Constraints, ou SBCs) à la formulation, en obtenant ainsi un narrowing. Le temps d'exécution et la dimension de l'arbre de Branch-and-Bound sont tous les deux meilleurs par rapport à la formulation originelle. La troisième application considérée dans cette thèse est le calcul de la relaxation convexe pour des problèmes multilinéaires, et la comparaison de la formulation ''primale'' avec celle obtenue par une représentation ''duale''. Bien que ces deux relaxations soient déjà connues, il est intéressant de voir que la relaxation duale conduit à des meilleures performances de calcul.
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Bundfuss, Stefan. "Copositive matrices, copositive programming, and applications." Tönning Lübeck Marburg Der Andere Verl, 2009. http://d-nb.info/994323700/04.
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Reeves, Laurence H. "Mathematical Programming Applications in Agroforestry Planning." DigitalCommons@USU, 1991. https://digitalcommons.usu.edu/etd/6495.
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Agroforestry as a sustainable production system has been recognized as a land use system with the potential to slow encroachment of agriculture onto forested lands in developing countries. However, the acceptance of nontraditional agroforestry systems has been hampered in some areas due to the risk-averse nature of rural agriculturalists. By explicitly recognizing risk in agroforestry planning, a wider acceptance of agroforestry is possible. This thesis consists of a collection of three papers that explore the potential of modern stock portfolio theory to reduce financial risk in agroforestry planning.
The first paper presents a theoretical framework that incorporates modern stock portfolio theory through mathematical programming. This framework allows for the explicit recognition of financial risk by using a knowledge of past net revenue trends and fluctuations for various cropping systems, with the assumption that past trend behavior is indicative of future behavior. The paper demonstrates how financial risk can be reduced by selecting cropping systems with stable and/or negatively correlated net revenues, thereby reducing the variance of future net revenues.
Agroforestry systems generally entail growing simultaneously some combination of plant and/or animal species. As a result, interactions between crops usually cause crop yields within systems to deviate from what would be observed under monocultural conditions, thus requiring some means of incorporating these interactions into mathematical models.
The second paper presents two approaches to modeling such interactions, depending on the nature of the interaction. The continuous system approach is appropriate under conditions where yield interactions are linear between crops and allows for a continuous range of crop mixtures. The discrete system approach should be used where nonlinear interactions occur. Under this second approach, decision variables are defined as fixed crop mixtures with known yields.
In the third paper, the techniques presented above were applied to a case study site in Costa Rica. Using MOTAD programming and a discrete system approach, a set of minimum-risk farm plans were derived for a hypothetical farm. For the region studied, results indicate that reductions in risk require substantial reductions in expected net revenue.
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Mabrouk, Emad Hamdy Ahmed. "Meta-Heuristics Programming and Its Applications." 京都大学 (Kyoto University), 2011. http://hdl.handle.net/2433/142132.
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Ye, Kai. "Applications of semidefinite programming in finance." Thesis, Imperial College London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.508489.
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Taha, Walid. "Multi-Stage Programming : Its Theory and Applications." Doctoral thesis, Oregon Graduate Institute of Science and Technology, 1999. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-15052.
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MetaML is a statically typed functional programming language with special support for programgeneration. In addition to providing the standard features of contemporary programminglanguages such as Standard ML, MetaML provides three staging annotations. These staging annotationsallow the construction, combination, and execution of object-programs.Our thesis is that MetaML's three staging annotations provide a useful, theoretically soundbasis for building program generators. This dissertation reports on our study of MetaML's stagingconstructs, their use, their implementation, and their formal semantics. Our results include anextended example of where MetaML allows us to produce ecient programs, an explanation ofwhy implementing these constructs in traditional ways can be challenging, two formulations ofMetaML's semantics, a type system for MetaML, and a proposal for extending MetaML with atype construct for closedness.The dissertation consolidates a number of previous publications by the author, includingMetaML's type systems and big-step semantics. The presentation is new. The proposed solutionto an implementation problem and the reduction semantics for MetaML's three staging constructsare also new.
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Tejedor, Saavedra Enric. "Programming and parallelising applications for distributed infrastructures." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/129576.
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The last decade has witnessed unprecedented changes in parallel and distributed infrastructures. Due to the diminished gains in processor performance from increasing clock frequency, manufacturers have moved from uniprocessor architectures to multicores; as a result, clusters of computers have incorporated such new CPU designs. Furthermore, the ever-growing need of scienti c applications for computing and storage capabilities has motivated the appearance of grids: geographically-distributed, multi-domain infrastructures based on sharing
of resources to accomplish large and complex tasks. More recently, clouds have emerged by combining virtualisation technologies, service-orientation and business models to deliver IT resources on demand over the Internet.
The size and complexity of these new infrastructures poses a challenge for programmers to exploit them. On the one hand, some of the di culties are inherent to concurrent and distributed programming themselves, e.g. dealing with thread creation and synchronisation, messaging, data partitioning and transfer, etc. On the other hand, other issues are related to the singularities of each scenario, like the heterogeneity of Grid middleware and resources or the risk of vendor lock-in when writing an application for a particular Cloud provider.
In the face of such a challenge, programming productivity - understood as a tradeo between programmability and performance - has become crucial for software developers. There is a strong need for high-productivity programming models and languages, which should provide simple means for writing parallel and distributed applications that can run on current infrastructures without sacri cing performance.
In that sense, this thesis contributes with Java StarSs, a programming model and runtime system for developing and parallelising Java applications on distributed infrastructures. The model has two key features: first, the user programs in a fully-sequential standard-Java fashion - no parallel construct, API call or pragma must be included in the application code; second, it is completely infrastructure-unaware, i.e. programs do not contain any details about deployment or resource management, so that the same application can run in di erent
infrastructures with no changes. The only requirement for the user is to select the application tasks, which are the model's unit of parallelism. Tasks can be either regular Java methods or web service operations, and they can handle any data type supported by the Java language, namely les, objects, arrays and primitives. For the sake of simplicity of the model, Java StarSs shifts the burden of parallelisation from the programmer to the runtime system. The runtime is responsible from modifying the original application to make it create asynchronous
tasks and synchronise data accesses from the main program. Moreover, the implicit inter-task concurrency is automatically found as the application executes, thanks to a data dependency detection mechanism that integrates all the Java data types.
This thesis provides a fairly comprehensive evaluation of Java StarSs on three di erent distributed scenarios: Grid, Cluster and Cloud. For each of them, a runtime system was designed and implemented to exploit their particular characteristics as well as to address their issues, while keeping the infrastructure unawareness of the programming model. The evaluation compares Java StarSs against state-of-the-art solutions, both in terms of programmability and performance, and demonstrates how the model can bring remarkable productivity to programmers of parallel distributed applications.
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Poojari, C. A. "Stochastic programming : models, solution methods and applications." Thesis, Brunel University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247549.
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Hsiung, Kan-Lin. "Geometric programming under uncertainty with engineering applications /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.
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Yee-King, Matthew John. "Automatic sound synthesizer programming : techniques and applications." Thesis, University of Sussex, 2011. http://sro.sussex.ac.uk/id/eprint/7612/.
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The aim of this thesis is to investigate techniques for, and applications of automatic sound synthesizer programming. An automatic sound synthesizer programmer is a system which removes the requirement to explicitly specify parameter settings for a sound synthesis algorithm from the user. Two forms of these systems are discussed in this thesis: tone matching programmers and synthesis space explorers. A tone matching programmer takes at its input a sound synthesis algorithm and a desired target sound. At its output it produces a configuration for the sound synthesis algorithm which causes it to emit a similar sound to the target. The techniques for achieving this that are investigated are genetic algorithms, neural networks, hill climbers and data driven approaches. A synthesis space explorer provides a user with a representation of the space of possible sounds that a synthesizer can produce and allows them to interactively explore this space. The applications of automatic sound synthesizer programming that are investigated include studio tools, an autonomous musical agent and a self-reprogramming drum machine. The research employs several methodologies: the development of novel software frameworks and tools, the examination of existing software at the source code and performance levels and user trials of the tools and software. The main contributions made are: a method for visualisation of sound synthesis space and low dimensional control of sound synthesizers; a general purpose framework for the deployment and testing of sound synthesis and optimisation algorithms in the SuperCollider language sclang; a comparison of a variety of optimisation techniques for sound synthesizer programming; an analysis of sound synthesizer error surfaces; a general purpose sound synthesizer programmer compatible with industry standard tools; an automatic improviser which passes a loose equivalent of the Turing test for Jazz musicians, i.e. being half of a man-machine duet which was rated as one of the best sessions of 2009 on the BBC's 'Jazz on 3' programme.
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Luo, Xiaodong. "Continuous linear programming : theory, algorithms and applications." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/10591.
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Chen, Jodie Lian. "Chorus : end user programming of social applications." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112902.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references (page 65).
Chorus is an end-user programming tool for building mobile social applications, much in the spirit of HyperCard¹ but reimagined for modern cloud-based applications on smart phones. Chorus innovates in two dimensions: first, by supporting collaboration via "social datatypes" that define a shared structured document; second, by providing a simple user interfaces on smartphones that support interacting with and designing these documents. This thesis reports on the design challenges encountered in building these two user interfaces and the solutions that were explored. The primary contributions of this research are: 1) techniques for visualizing and navigating a complex hierarchical document on a phone, and 2) supporting WYSIWYG design of a complex data artifact within the UI constraints of a phone. Qualitative user testing was used to guide and evaluate the design decisions, indicating both successes and problems requiring further work.
by Jodie Lian Chen.
M. Eng.
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Wong, Eric M. Eng Massachusetts Institute of Technology. "Optimizations in stream programming for multimedia applications." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/85522.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 85-89).
Multimedia applications are the most dominant workload in desktop and mobile computing. Such applications regularly process continuous sequences of data and can be naturally represented under the stream programming domain to take take advantage of domain-specific optimizations. Exploiting characteristics specific to multimedia programs can provide further significant impact on performance for this class of programs. This thesis identifies many multimedia applications that maintain induction variable state, which directly inhibits data parallelism for the program. We demonstrates it is essential to recognize and parallelize filters with induction variable state to enable scalable parallelization. We eliminate such state by introducing a new language construct that automatically returns the current iteration number of a target filter. This thesis also exploits the fact that multimedia applications are tolerant in the accuracy of the program output. We apply a memoization technique that exploits this tolerance and the repetitive nature of multimedia data. We provide a runtime system that automatically tunes the memoization capabilities for performance and output quality. These optimizations are implemented in the StreamIt programmming language. The necessity of parallelizing induction variable state and performance improvements and quality control of our memoization technique is demonstrated by a case study of the MPEG benchmark.
by Eric Wong.
M. Eng.
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Phillips, Brent M. (Brent Michael). "A distributed programming system for media applications." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36960.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 104-106).
by Brent M. Phillips.
M.S.
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Glen, Andrew Gordon. "A probability programming language: Development and applications." W&M ScholarWorks, 1998. https://scholarworks.wm.edu/etd/1539623920.
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A probability programming language is developed and presented; applications illustrate its use. Algorithms and generalized theorems used in probability are encapsulated into a programming environment with the computer algebra system Maple to provide the applied community with automated probability capabilities. Algorithms of procedures are presented and explained, including detailed presentations on three of the most significant procedures. Applications that encompass a wide range of applied topics including goodness-of-fit testing, probabilistic modeling, central limit theorem augmentation, generation of mathematical resources, and estimation are presented.
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Chung, Wai Hing. "Teaching computer control applications : a programming approach." Thesis, University of Edinburgh, 1986. http://hdl.handle.net/1842/19628.
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Wang, Xia. "Applications of genetic algorithms, dynamic programming, and linear programming to combinatorial optimization problems." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8778.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2008.Thesis research directed by: Applied Mathematics & Statistics, and Scientific Computation Program. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Albrecht, Conan Carl. "Programming framework supporting the rapid application development of highly-interactive, collaborative applications." Diss., The University of Arizona, 2000. http://hdl.handle.net/10150/558708.
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Business team collaboration in the future will increasingly take place in an
environment where everything is potentially distributed. Traditional group support systems
have been LAN-based and have not ported easily to distributed, Internet-based products.
Rather, distributed group support systems require new architectures if they are to support the
same type of real-time, high-collaboration environments that traditional systems have.
This dissertation describes the development of a server architecture and programming
model to support the rapid application development of real-time, distributed, and
collaborative applications. Since the efficiency, robustness, and scalability of these
applications are handled by the server, complex applications can be developed in very short
production cycles.
Background literature presented in the dissertation includes a taxonomy of distributed
networking and data sharing methods, models of dialog independence, and messaging
methods. Many different prototype and real systems are presented, analyzed, and compared
with the Collaborative Server in this dissertation. The Systems Development methodology
is applied to this research domain.
A prototype system-the “Collaborative Server”-is developed, including a unique data
persistence and replication scheme based upon a central Property object. Properties are
created in hierarchical trees to form the “scaffolding” for collaborative applications. Each
Property governs a single value, or datum, and controls the access, replication, security,
viewing, locking, and persistence of its value. Properties are layered with predefined or
custom child indices.
A new systems development methodology, based upon the Waterfall method but
tailored for the Collaborative Server, is presented. The efficiency and effectiveness of this
methodology is analyzed using a simulated example and two case studies.
The research contribution of this dissertation is the Collaborative Server. The basis
of this server is the Property concept, including the methodology changes it effects, the
efficiencies and application stability it produces, and the specialized messaging system it
allows. Required programmer knowledge is significantly reduced when applications are built
upon the Collaborative Server. In addition, the presented examples and case studies show
significant decreases in code size and in time-to-market for their respective applications.
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Byrd, William E. "Relational programming in miniKanren techniques, applications, and implementations /." [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3380156.
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Thesis (Ph.D.)--Indiana University, Dept. of Computer Science, 2009.Title from PDF t.p. (viewed on Jul 20, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: B, page: 7659. Adviser: Daniel P. Friedman.
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Shields, Matthew S. "Visual programming environments for multi-disciplinary distributed applications." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55952/.
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A Problem Solving Environment is a complete, integrated computing environment for composing, compiling and running applications in a specific problem area or domain. A Visual Programming Environment is one possible front end to a problem solving environment. It applies the visual programming paradigms of "point and click" and "drag and drop", via a Graphical User Interface, to the various constituent components that are used to assemble an application. The aim of the problem solving environment presented here is to provide the ability to build up scientific applications by connecting, or plugging, software components together and to provide an intuitive way to construct scientific applications. Problem solving environments promise a totally new user environment for computational scientists and engineers. In this new paradigm, individual programs combined to solve a problem in their given area of expertise, are wrapped as components within an integrated system that is both powerful and easy to use. This thesis aims to address: problems in code reuse the combination of different codes in new ways and problems with underlying system familiarity and distribution. This is achieved by abstracting application composition using visual programming techniques. The work here focuses on a prototype environment using a number of demonstration problems from multi-disciplinary problem domains to illustrate some of the main difficulties in building problem solving environments and some possible solutions. A novel approach to code wrapping, component definition and application specification is shown, together with timing and usage comparisons that illustrate that this approach can be used successfully to help scientists and engineers in their daily work.
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Thar, M. S. "Intention-oriented programming model for autonomic cloud applications." Thesis, Liverpool John Moores University, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526921.
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Van, ackooij Wim Stefanus. "Chance Constrained Programming : with applications in Energy Management." Phd thesis, Ecole Centrale Paris, 2013. http://tel.archives-ouvertes.fr/tel-00978519.
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In optimization problems involving uncertainty, probabilistic constraints are an important tool for defining safety of decisions. In Energy management, many optimization problems have some underlying uncertainty. In particular this is the case of unit commitment problems. In this Thesis, we will investigate probabilistic constraints from a theoretical, algorithmic and applicative point of view. We provide new insights on differentiability of probabilistic constraints and on convexity results of feasible sets. New variants of bundle methods, both of proximal and level type, specially tailored for convex optimization under probabilistic constraints, are given and convergence shown. Both methods explicitly deal with evaluation errors in both the gradient and value of the probabilistic constraint. We also look at two applications from energy management: cascaded reservoir management with uncertainty on inflows and unit commitment with uncertainty on customer load. In both applications uncertainty is dealt with through the use of probabilistic constraints. The presented numerical results seem to indicate the feasibility of solving an optimization problem with a joint probabilistic constraint on a system having up to 200 constraints. This is roughly the order of magnitude needed in the applications. The differentiability results involve probabilistic constraints on uncertain linear and nonlinear inequality systems. In the latter case a convexity structure in the underlying uncertainty vector is required. The uncertainty vector is assumed to have a multivariate Gaussian or Student law. The provided gradient formulae allow for efficient numerical sampling schemes. For probabilistic constraints that can be rewritten through the use of Copulae, we provide new insights on convexity of the feasible set. These results require a generalized concavity structure of the Copulae, the marginal distribution functions of the underlying random vector and of the underlying inequality system. These generalized concavity properties may hold only on specific sets.
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CERQUEIRA, CRISTINA URURAHY DA FONTOURA. "A MULTILANGUAGE PROGRAMMING MODEL FOR GEOGRAPHICALLY DISTRIBUTED APPLICATIONS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=4649@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRONeste trabalho propomos usar o ALua, um mecanismo de comunicação orientado a eventos, baseado na linguagem interpretada Lua, para coordenação e desenvolvimento de aplicações paralelas distribuídas. ALua é um modelo de programação dual para aplicações paralelas distribuídas, que age como elemento de ligação, permitindo que partes pré- compiladas do programa sejam executadas em diferentes máquinas. Novas tecnologias em programação paralela, como computação em grade, e o interesse atual em computação distribuída para redes geográficas demandam novos níveis de flexibilidade, como o uso de estratégias de adaptação e a habilidade para um usuário interferir em uma computação sem a necessidade de interrompê-la. Além disso, devido a sua natureza assíncrona, a programação dirigida a eventos oferece um modelo apropriado para ambiente sujeitos a falhas e retardos, que são freqüentes no contexto de redes geográficas. Neste trabalho, mostramos que o ALua pode trazer a flexibilidade desejada, através de mecanismos de adaptação e monitoramento não só de aplicações, mas do próprio ambiente de execução, e ainda tirar proveito de sua natureza interpretada para permitir a intervenção do usuário na aplicação mesmo durante a sua execução.
In this work we propose the use of Alua, an event-driven communication mechanism for coordinating and developing distributed parallel applications, based on the interpreted language Lua. Alua adopts a multilinguage programming model for distributed parallel applications, acting as a gluing element among precompiled program parts running on different machines. New developments in parallel programming, such as Grid computing, and current interest in wide-area distributed computing demand new levels of flexibility, such as the use of adaptive strategies and the ability for an user to interfer with a computation without having to stop it. Furthermore, because of its asynchronous nature, event-driven programming provides a suitable model for environments subject to failures and delays that are frequent in the context of geographically distributed computing. In this work we show that ALua can achieve the required flexibility through mechanisms for monitoring and adapting not only applications, but also the execution environment, and also exploit its interpretive nature to allow the programmer to modify the behavior of the application during its execution.
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Pinder, Robert William 1977. "Applications of genetic programming to parallel system optimization." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86507.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 81-84).
by Robert William Pinder.
M.Eng.
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Szularz, Marek. "Quadratic programming with constant norm with parallel applications." Thesis, Kingston University, 1991. http://eprints.kingston.ac.uk/20556/.
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This thesis is concerned with the problem of minimizing a quadratic function defined on an ellipsoid, and subject to the set of linear inequality constraints. An original method is proposed, a method which generates the descent flow on the spiral, the curve on the surface of the constraining ellipsoid, characterized locally by the steepest descent of the objective function. The spiral is constructed discretely in a number of points which are the solutions of the sequence of certain artificially constrained subproblems. The properties of the spiral are studied extensively to show that the associated descent flow can be divided into three categories of the regular, separated and multiple descent flow. Particular attention is devoted to the case of the separated descent flow, which involves the discontinuity of the spiral and may pose certain difficulties in the search for the solution. The important and the original part of the thesis is also the issue of all local minima of the equality constrained version of the problem. The identification of all such minima is vital to the main problem and the corresponding method. The method which may find many practical applications, has been inspired by the opportunities given by a massively parallel computer, namely the Distributed Array Processor, although the method can find the applications in other parallel environments. The algorithm has been implemented in DAP Fortran-Plus, and a series of numerical examples is presented, some of them of practical importance in structural engineering.
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Van, Ackooij Wim. "Chance Constrained Programming : with applications in Energy Management." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2013. http://www.theses.fr/2013ECAP0071/document.
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Les contraintes en probabilité constituent un modèle pertinent pour gérer les incertitudes dans les problèmes de décision. En management d’énergie de nombreux problèmes d’optimisation ont des incertitudes sous-jacentes. En particulier c’est le cas des problèmes de gestion de la production au court-terme. Dans cette Thèse, nous investiguons les contraintes probabilistes sous l’angle théorique, algorithmique et applicative. Nous donnons quelques nouveaux résultats de différentiabilité des contraintes en probabilité et de convexité des ensembles admissibles. Des nouvelles variantes des méthodes de faisceaux « proximales » et « de niveaux » sont spécialement mises au point pour traiter des problèmes d’optimisation convexe sous contrainte en probabilité. Ces algorithmes gèrent en particulier, les erreurs d’évaluation de la contrainte en probabilité, ainsi que son gradient. La convergence vers une solution du problème est montrée. Enfin, nous examinons deux applications : l’optimisation d’une vallée hydraulique sous incertitude sur les apports et l’optimisation d’un planning de production sous incertitude sur la demande. Dans les deux cas nous utilisons une contrainte en probabilité pour gérer les incertitudes. Les résultats numériques présentés semblent montrer la faisabilité de résoudre des problèmes d’optimisation avec une contrainte en probabilité jointe portant sur un système de environ 200 contraintes. Il s’agit de l’ordre de grandeur nécessaire pour les applications. Les nouveaux résultats de différentiabilité concernent à la fois des contraintes en probabilité portant sur des systèmes linéaires et non-linéaires. Dans le deuxième cas, la convexité dans l’argument représentant le vecteur incertain est requise. Ce vecteur est supposé suivre une loi Gaussienne ou Student multi-variée. Les formules de gradient permettent l’application directe d’un schéma d’évaluation numérique efficient. Pour les contraintes en probabilité qui peuvent se réécrire à l’aide d’une Copule, nous donnons de nouveau résultats de convexité pour l’ensemble admissibles. Ces résultats requirent la concavité généralisée de la Copule, les distributions marginales sous-jacents et du système d’incertitude. Il est suffisant que ces propriétés de concavité généralisée tiennent sur un ensemble spécifiqueIn optimization problems involving uncertainty, probabilistic constraints are an important tool for defining safety of decisions. In Energy management, many optimization problems have some underlying uncertainty. In particular this is the case of unit commitment problems. In this Thesis, we will investigate probabilistic constraints from a theoretical, algorithmic and applicative point of view. We provide new insights on differentiability of probabilistic constraints and on convexity results of feasible sets. New variants of bundle methods, both of proximal and level type, specially tailored for convex optimization under probabilistic constraints, are given and convergence shown. Both methods explicitly deal with evaluation errors in both the gradient and value of the probabilistic constraint. We also look at two applications from energy management: cascaded reservoir management with uncertainty on inflows and unit commitment with uncertainty on customer load. In both applications uncertainty is dealt with through the use of probabilistic constraints. The presented numerical results seem to indicate the feasibility of solving an optimization problem with a joint probabilistic constraint on a system having up to 200 constraints. This is roughly the order of magnitude needed in the applications. The differentiability results involve probabilistic constraints on uncertain linear and nonlinear inequality systems. In the latter case a convexity structure in the underlying uncertainty vector is required. The uncertainty vector is assumed to have a multivariate Gaussian or Student law. The provided gradient formulae allow for efficient numerical sampling schemes. For probabilistic constraints that can be rewritten through the use of Copulae, we provide new insights on convexity of the feasible set. These results require a generalized concavity structure of the Copulae, the marginal distribution functions of the underlying random vector and of the underlying inequality system. These generalized concavity properties may hold only on specific sets
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Cymer, Radosław [Verfasser]. "Applications of matching theory in constraint programming / Radosław Cymer." Hannover : Technische Informationsbibliothek und Universitätsbibliothek Hannover (TIB), 2014. http://d-nb.info/1050990498/34.
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Bandini, Alessandro. "Programming and Deployment of Cloud-based Data Analysis Applications." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13803/.
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Cloud Computing constitutes a model capable of enabling the network access in a shared, practical and on demand of different computational resources like networks, memory, application or services.
This work has as goal the explanation of the project made within Cloud Computing. After an introduction of the theory that lies behind Cloud computing's technologies, there is the practical part of the the work, starting from a more specific platform, Hadoop, which allows storage and data analysis and then moving to more general purpose platforms, Amazon Web Services and Google App Engine, where different types of services have been tried. The major part of the project is based on Google App Engine, where storage and computational services have been used to run MapReduce jobs. MapReduce is a different programming approach for solving data analysis problems, that is suited for big data. The first jobs are written in python, an imperative programming language. Later on, a functional approach on the same problems has been tried, with the Scala language and Spark platform, to compare the code.
As Cloud computing is mainly used to host websites, a simple site was developed as integral part of the work. The development of the site is not explained as it goes beyond this thesis' main focus, only the relevant aspects will be treated.
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Howse, Samuel. "Dynamic programming problems, neural network solutions and economic applications." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0009/MQ60678.pdf.
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Axehill, Daniel. "Applications of Integer Quadratic Programming in Control and Communication." Licentiate thesis, Linköping : Dept. of Electrical Engineering, Linköping University, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5263.
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Mahar, Mumtaz Hussain. "Network optimization and its applications to discrete programming problems." Thesis, Brunel University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294509.
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Chen, Fei, and 陳飛. "Linear programming techniques for algorithms with applications in economics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206329.
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We study algorithms and models for several economics-related problems from the perspective of linear programming.
In network bargaining games, stable and balanced outcomes have been investigated in previous work. However, existence of such outcomes requires that the linear program relaxation of a certain maximum matching problem has integral optimal solution. We propose an alternative model for network bargaining games in which each edge acts as a player, who proposes how to split the weight of the edge among the two incident nodes. We show that the distributed protocol by Kanoria et. al can be modified to be run by the edge players such that the configuration of proposals will converge to a pure Nash Equilibrium, without the linear program integrality gap assumption. Moreover, ambiguous choices can be resolved in a way such that there exists a Nash Equilibrium that will not hurt the social welfare too much.
In the oblivious matching problem, an algorithm aims to find a maximum matching while it can only makes (random) decisions that are essentially oblivious to the input graph. Any greedy algorithm can achieve performance ratio 0:5, which is the expected number of matched nodes to the number of nodes in a maximum matching. We revisit the Ranking algorithm using the linear programming framework, where the constraints of the linear program are given by the structural properties of Ranking. We use continuous linear program relaxation to analyze the limiting behavior as the finite linear program grows. Of particular interest are new duality and complementary slackness characterizations that can handle monotone constraints and mixed evolving and boundary constraints in continuous linear program, which enable us to achieve a theoretical ratio of 0:523 on arbitrary graphs.
The J-choice K-best secretary problem, also known as the (J;K)-secretary problem, is a generalization of the classical secretary problem. An algorithm for the (J;K)-secretary problem is allowed to make J choices and the payoff to be maximized is the expected number of items chosen among the K best items. We use primal-dual continuous linear program techniques to analyze a class of infinite algorithms, which are general enough to capture the asymptotic behavior of the finite model with large number of items. Our techniques allow us to prove that the optimal solution can be achieved by a (J;K)-threshold algorithm, which has a nice \rational description" for the case K = 1.published_or_final_version
Computer Science
Doctoral
Doctor of Philosophy
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Rayaprolu, Srinivas. "Using COM object programming for enhanced library search applications." Cincinnati, Ohio : University of Cincinnati, 2001. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=ucin1029441248.
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LONGO, HUMBERTO JOSE. "INTEGER PROGRAMMING TECHNIQUES AND APPLICATIONS TO VEHICLE ROUTING PROBLEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=6029@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIORUNIVERSIDADE FEDERAL DE GOIÁS
A natureza intrinsicamente combinatorial de muitos problemas advindos da área de logística de transportes, em especial aqueles que dizem respeito ao uso racional de frotas de veículos, sugere que boa parte dos mesmos pode ser formulada e resolvida como um problema de programação linear inteira. Contudo, a maioria dos algoritmos até o momento disponíveis não consegue encontrar, em tempos computacionais aceitáveis, a solução ótima para instâncias de porte razoável. O objeto de estudo desta tese é a exploração de técnicas mais recentes da área de programação linear inteira e suas aplicações a problemas de roteamento de veículos. A primeira parte da tese descreve, além das técnicas básicas de decomposição de problemas de programação linear e linear inteira e de geração de colunas, uma proposta de reformulação de problemas de programação linear inteira alternativa àquela que gera o tradicional problema mestre de Dantzig-Wolfe, geralmente utilizados em abordagens por geração de colunas. A resolução de problemas de programação linear inteira neste contexto é tratada em seguida, com a descrição do algoritmo branch-and-bound e das variações branch-and-cut, branch-and-price e branch-and-cut-and-price. Na segunda parte da tese, inicialmente, é apresentada a técnica denominada de Geração Projetada de Colunas e sua aplicação ao problema de Roteamento de Veículos com Restrição de Capacidade. Em seguida é abordada a resolução do problema de Roteamento de Veículos sobre Arcos, através de sua transformação ao primeiro problema citado e uso de um algoritmo branch-and- cut-and-price. Finalmente, é proposto um novo problema na área de redistribuição de veículos de aluguel, para o qual é proposta uma formulação segundo uma abordagem por geração de colunas. São apresentados, ainda, procedimentos para a geração de colunas e resultados computacionais obtidos com um algoritmo branch-and-price para essa formulação.
Optimization techniques have an important role in Transportation Logistics. The combinatorial nature of the problems related to this area suggests integer programming as a natural approach to their resolution. Nevertheless there are many cases where even instances of reasonable size still beyond the resolution capability of the current known algorithms. The success of the known algorithms have therefore been limited. This can be justified by the fact the most of them leave important recent advances in the combinatorial optimization field unexplored. Some of these new techniques and their applications are the main subject of this thesis. In the first part, the basic decomposition techniques for linear and integer programming problems as well as the related column generation approach is addressed. This is followed by the presentation of a reformulation technique for linear and integer programming which is alternative to the well known Dantzig-Wolfe master program. The new possibilities coming from this approach are explored and the resulting consequences to the standard branch-and- bound algorithm and its variations branch-and-cut, branch-and- price and branchand- cut-and-price are presented. The second part of this text addresses the application of the metodologies described in part one to routing problems where capacity constraints are considered. First, a techinque named Projected Column Generation is described in the context of the Capacitated Vehicle Routing Problem. Then, it is presented a new transformation from the Capacitated Arc Routing Problem to the Capacitated Vehicle Routing Problem as well as a tailored branch-and-cut-and-price to solve this problem. Finally, a new problem in vehicle redistrubution is described together with a column generation approach for its resolution. Computational results for all applications are presented.
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Valenti, Mario J. (Mario James) 1976. "Approximate dynamic programming with applications in multi-agent systems." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40330.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
MIT Institute Archives copy: contains CDROM of thesis in .pdf format.
Includes bibliographical references (p. 151-161).
This thesis presents the development and implementation of approximate dynamic programming methods used to manage multi-agent systems. The purpose of this thesis is to develop an architectural framework and theoretical methods that enable an autonomous mission system to manage real-time multi-agent operations. To meet this goal, we begin by discussing aspects of the real-time multi-agent mission problem. Next, we formulate this problem as a Markov Decision Process (MDP) and present a system architecture designed to improve mission-level functional reliability through system self-awareness and adaptive mission planning. Since most multi-agent mission problems are computationally difficult to solve in real-time, approximation techniques are needed to find policies for these large-scale problems. Thus, we have developed theoretical methods used to find feasible solutions to large-scale optimization problems. More specifically, we investigate methods designed to automatically generate an approximation to the cost-to-go function using basis functions for a given MDP. Next, these these techniques are used by an autonomous mission system to manage multi-agent mission scenarios. Simulation results using these methods are provided for a large-scale mission problem. In addition, this thesis presents the implementation of techniques used to manage autonomous unmanned aerial vehicles (UAVs) performing persistent surveillance operations. We present an indoor multi-vehicle testbed called RAVEN (Real-time indoor Autonomous Vehicle test ENvironment) that was developed to study long-duration missions in a controlled environment.
(cont.) The RAVEN's design allows researchers to focus on high-level tasks by autonomously managing the platform's realistic air and ground vehicles during multi-vehicle operations, thus promoting the rapid prototyping of UAV technologies by flight testing new vehicle configurations and algorithms without redesigning vehicle hardware. Finally, using the RAVEN, we present flight test results from autonomous, extended mission tests using the technologies developed in this thesis. Flight results from a 24 hr, fully-autonomous air vehicle flight-recharge test and an autonomous, multi-vehicle extended mission test using small, electric-powered air vehicles are provided.
by Mario J. Valenti.
Ph.D.
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Jordan, Eric Michael. "Programming models for the development of interactive audio applications." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37764.
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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 59-63).
by Eric Michael Jordan.
M.S.
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Tuncbilek, Cihan H. "Polynomial and indefinite quadratic programming problems: algorithms and applications." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/39040.
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Macedo, Eloísa Catarina Monteiro de Figueiredo Amaral e. "Numerical study of regularity in semidefinite programming and applications." Doctoral thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16278.
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Doutoramento em MatemáticaThis thesis is devoted to the study of regularity in semidefinite programming (SDP), an important area of convex optimization with a wide range of applications. The duality theory, optimality conditions and methods for SDP rely on certain assumptions of regularity that are not always satisfied. Absence of regularity, i.e., nonregularity, may affect the characterization of optimality of solutions and SDP solvers may run into numerical difficulties, leading to unreliable results. There exist different notions associated to regularity. In this thesis, we study in particular, well-posedness, good behaviour and constraint qualifications (CQs), as well as relations among them. A widely used CQ in SDP is the Slater condition. This condition guarantees that the first order necessary optimality conditions in the Karush-Kuhn-Tucker formulation are satisfied. Current SDP solvers do not check if a problem satisfies the Slater condition, but work assuming its fulfilment. We develop and implement in MATLAB numerical procedures to verify if a given SDP problem is regular in terms of the Slater condition and to determine the irregularity degree in the case of nonregularity. Numerical experiments presented in this work show that the proposed procedures are quite effcient and confirm the obtained conclusions about the relationship between the Slater condition and other regularity notions. Other contribution of the thesis consists in the development and MATLAB implementation of an algorithm for generating nonregular SDP problems with a desired irregularity degree. The database of nonregular problems constructed using this generator is publicly available and can be used for testing new SDP methods and solvers. Another contribution of this thesis is concerned with an SDP application to data analysis. We consider a nonlinear SDP model and linear SDP relaxations for clustering problems and study their regularity. We show that the nonlinear SDP model is nonregular, while its relaxations are regular. We suggest a SDP-based algorithm for solving clustering and dimensionality reduction problems and implement it in R. Numerical tests on various real-life data sets confirm the fastness and efficiency of this numerical procedure.
Esta tese _e dedicada ao estudo de regularidade em programação semidefinida (SDP - semidefinite programming), uma importante área da optimização convexa com uma vasta gama de aplicações. A teoria de dualidade, condições de optimalidade e métodos para SDP assentam em certos pressupostos de regularidade que nem sempre são satisfeitos. A ausência de regularidade, isto é, não regularidade, pode afetar a caracterização da optimalidade de soluções e os solvers podem apresentar dificuldades numéricas, conduzindo a resultados pouco fiáveis. Existem diferentes noções associadas a regularidade. Nesta tese, estudamos em particular, os conceitos de problemas bem-postos, bem comportados e condições de qualificação de restrições (CQ - constraint qualifications), bem como as relações entre eles. Uma das CQs mais utilizadas em SDP é a condição de Slater. Esta condição garante que as condições de optimalidade de primeira ordem, conhecidas como condições de Karush-Kuhn-Tucker, estão satisfeitas. Os solvers atuais não verificam se um problema a resolver satisfaz a condição de Slater, mas trabalham nesse pressuposto. Desenvolvemos e implementamos em MATLAB procedimentos numéricos para verificar se um dado problema de SDP é regular em termos da condição de Slater e determinar o grau de irregularidade no caso de problemas não regulares. Os resultados das experiências numéricas apresentados neste trabalho mostram que os procedimentos propostos são eficientes e confirmam as conclusões obtidas sobre a relação entre a condição de Slater e outras noções de regularidade. Outra contribuição da tese consiste no desenvolvimento e na implementação em MATLAB de um procedimento numérico para gerar problemas de SDP não regulares com um determinado grau de irregularidade. A colecção de problemas não regulares construídos usando este gerador é de acesso livre e permite testar novos métodos e solvers para SDP. Uma outra contribuição desta tese está relacionada com uma aplicação de SDP em análise de dados. Consideramos um modelo de SDP não linear, bem como as suas relaxações lineares para problemas de clusterização, e estudamos a sua regularidade. Mostramos que o modelo não linear é não regular, enquanto que as suas relaxações são regulares. Sugerimos um algoritmo baseado em modelos de SDP para resolver problemas de clusterização e redução de dimensionalidade, e implementámo-lo em R. Os testes numéricos usando vários conjuntos de dados confirmam a rapidez e eficiência deste procedimento numérico.
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Dekkiche, Djamila. "Programming methodologies for ADAS applications in parallel heterogeneous architectures." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS388/document.
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La vision par ordinateur est primordiale pour la compréhension et l’analyse d’une scène routière afin de construire des systèmes d’aide à la conduite (ADAS) plus intelligents. Cependant, l’implémentation de ces systèmes dans un réel environnement automobile et loin d’être simple. En effet, ces applications nécessitent une haute performance de calcul en plus d’une précision algorithmique. Pour répondre à ces exigences, de nouvelles architectures hétérogènes sont apparues. Elles sont composées de plusieurs unités de traitement avec différentes technologies de calcul parallèle: GPU, accélérateurs dédiés, etc. Pour mieux exploiter les performances de ces architectures, différents langages sont nécessaires en fonction du modèle d’exécution parallèle. Dans cette thèse, nous étudions diverses méthodologies de programmation parallèle. Nous utilisons une étude de cas complexe basée sur la stéréo-vision. Nous présentons les caractéristiques et les limites de chaque approche. Nous évaluons ensuite les outils employés principalement en terme de performances de calcul et de difficulté de programmation. Le retour de ce travail de recherche est crucial pour le développement de futurs algorithmes de traitement d’images en adéquation avec les architectures parallèles avec un meilleur compromis entre les performances de calcul, la précision algorithmique et la difficulté de programmationComputer Vision (CV) is crucial for understanding and analyzing the driving scene to build more intelligent Advanced Driver Assistance Systems (ADAS). However, implementing CV-based ADAS in a real automotive environment is not straightforward. Indeed, CV algorithms combine the challenges of high computing performance and algorithm accuracy. To respond to these requirements, new heterogeneous circuits are developed. They consist of several processing units with different parallel computing technologies as GPU, dedicated accelerators, etc. To better exploit the performances of such architectures, different languages are required depending on the underlying parallel execution model. In this work, we investigate various parallel programming methodologies based on a complex case study of stereo vision. We introduce the relevant features and limitations of each approach. We evaluate the employed programming tools mainly in terms of computation performances and programming productivity. The feedback of this research is crucial for the development of future CV algorithms in adequacy with parallel architectures with a best compromise between computing performance, algorithm accuracy and programming efforts
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RAYAPROLU, SRINIVAS. "USING COM OBJECTS PROGRAMMING FOR ENHANCED LIBRARY SEARCH APPLICATIONS." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1029441248.
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Saleck, Pay Babak. "Decomposition Algorithms in Stochastic Integer Programming: Applications and Computations." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/5027.
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In this dissertation we focus on two main topics. Under the first topic, we develop a new framework for stochastic network interdiction problem to address ambiguity in the defender risk preferences. The second topic is dedicated to computational studies of two-stage stochastic integer programs. More specifically, we consider two cases. First, we develop some solution methods for two-stage stochastic integer programs with continuous recourse; second, we study some computational strategies for two-stage stochastic integer programs with integer recourse. We study a class of stochastic network interdiction problems where the defender has incomplete (ambiguous) preferences. Specifically, we focus on the shortest path network interdiction modeled as a Stackelberg game, where the defender (leader) makes an interdiction decision first, then the attacker (follower) selects a shortest path after the observation of random arc costs and interdiction effects in the network. We take a decision-analytic perspective in addressing probabilistic risk over network parameters, assuming that the defender's risk preferences over exogenously given probabilities can be summarized by the expected utility theory. Although the exact form of the utility function is ambiguous to the defender, we assume that a set of historical data on some pairwise comparisons made by the defender is available, which can be used to restrict the shape of the utility function. We use two different approaches to tackle this problem. The first approach conducts utility estimation and optimization separately, by first finding the best fit for a piecewise linear concave utility function according to the available data, and then optimizing the expected utility. The second approach integrates utility estimation and optimization, by modeling the utility ambiguity under a robust optimization framework following \cite{armbruster2015decision} and \cite{Hu}. We conduct extensive computational experiments to evaluate the performances of these approaches on the stochastic shortest path network interdiction problem. In third chapter, we propose partition-based decomposition algorithms for solving two-stage stochastic integer program with continuous recourse. The partition-based decomposition method enhance the classical decomposition methods (such as Benders decomposition) by utilizing the inexact cuts (coarse cuts) induced by a scenario partition. Coarse cut generation can be much less expensive than the standard Benders cuts, when the partition size is relatively small compared to the total number of scenarios. We conduct an extensive computational study to illustrate the advantage of the proposed partition-based decomposition algorithms compared with the state-of-the-art approaches. In chapter four, we concentrate on computational methods for two-stage stochastic integer program with integer recourse. We consider the partition-based relaxation framework integrated with a scenario decomposition algorithm in order to develop strategies which provide a better lower bound on the optimal objective value, within a tight time limit.
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De, Martini Alessandro. "Intuitive programming of mobile manipulation applications : A functional and modular GUI architecture for End-User robot programming." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303006.
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Mobile manipulators are changing the way companies and industries complete their work. Untrained end users risk facing unfunctional and nonuser- friendly Graphical User Interfaces. Recently, there has been shortages of people and talent in the heathcare industry where these applications would benefit in being used to accomplish easy and low level tasks. All these reasons contribute to the need of finding functional robot-user ways of communicating that allow the expansion of mobile manipulation applications. This thesis addresses the problem of finding an intuitive way to deploy a mobile manipulator in a laboratory environment. This thesis has analyzed whether it is possible to permit the user to work with a manipulator efficiently and without too much effort via a functional graphical user interface. Creating a modular interface based on user needs is the innovation value of this work. It allows the expansion of mobile manipulator applications that increases the number of possible users. To accomplish this purpose a Graphical User Interface application is proposed using an explanatory research strategy. First, user data was acquired using an ad hoc research survey and mixed with literature implementations to create the right application design. Then, an iterative implementation based on code-creation and tests was used to design a valuable solution. Finally, the results from an observational user study with non-roboticist programmers are presented. The results were validated with the help of 10 potential end users and a validation matrix. This demonstrated how the system is both functional and user-friendly for novices, but also expressive for experts.Mobilmanipulatorer förändrar sättet som företag och industrier utför sitt arbete. Otränade slutanvändare och särskilt de utan programmeringskunskap kommer att bemötas av icke-funktionella och användarovänliga grafiska användargränssnitt. Den senaste tiden har det varit brist på specialiserad personal inom hälsovårdsindustrin som har resulterat i ett beroende på dessa applikationer för att genomföra enkla uppgifter samt uppgifter på låg nivå. Alla dessa faktorer bidrar till det ökande behovet att hitta ett funktionellt sätt att kommunicera mellan robot och slutanvändare vilket tillåter expansionen av mobilmanipulatorapplikationer. Arbetet som beskrivs i denna avhandling adresserar problemet att finna ett intuitivt sätt att använda en mobilmanipulator i ett laboratoriemijö. Möjligheten att tillåta användaren att på ett enkelt och effektivt sätt arbeta med en manipulator via ett funtionellt grafiskt användargränssnitt analyseras. Innovationsvärdet och detta examensarbetes bidrag till nuvarande kunskap betraktar möjligheten att skapa ett modulärt gränssnitt baserat på användares behov. Detta möjliggör expansionen av mobilmanipulatörers applikation vilket ökar antalet möjliga användare. En förklarande forskningsstrategi används för att föreslå en grafisk användargränssnittsapplikation för att uppnå detta mål. Först användes data från ad hoc-undersökningar blandat med litteraturimplementeringar för att skapa den rätta applikationsdesignen. En iterativ implementering baserad på kodskapande samt tester användes sedan för att designa en värdefull lösning redo att testas. Slutligen presenteras resultat från en användarobservationsstudie med icke-robotikprogrammerare. De insamlade resultaten som samlades in under valideringsstadiet tack vare en grupp bestående av tio potentiella slutanvändare har analyserats genom användandet av en valideringsmatris som är baserad på tre parametrar. Detta demonstrerade hur systemet är både funktionellt och användarvänligt för nybörjare men också expressivt för experter.