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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
111

Operation of Booster Disinfection Systems: From Offline Design to Online Control

Propato, Marco 31 March 2004 (has links)
No description available.
112

A Comparative Analysis of an Interior-point Method and a Sequential Quadratic Programming Method for the Markowitz Portfolio Management Problem

Xiao, Zhifu 12 August 2016 (has links)
No description available.
113

Multicategory psi-learning and support vector machine

Liu, Yufeng 18 June 2004 (has links)
No description available.
114

Optimization Models and Algorithms for Pricing in e-Commerce

Shams-Shoaaee, Seyed Shervin January 2020 (has links)
With the rise of online retailer giants like Amazon, and enhancements in internet and mobile technologies, online shopping is becoming increasingly popular. This has lead to new opportunities in online price optimization. The overarching motivation and theme of this thesis is to review these opportunities and provide methods and models in the context of retailers' online pricing decisions. In Chapter 2 a multi-period revenue maximization and pricing optimization problem in the presence of reference prices is formulated as a mixed integer nonlinear program. Two algorithms are developed to solve the optimization problem: a generalized Benders' decomposition algorithm and a myopic heuristic. This is followed by numerical computations to illustrate the effciency of the solution approaches as well as some managerial pricing insights. In Chapter 3 a data-driven quadratic programming optimization model for online pricing in the presence of customer ratings is proposed. A new demand function is developed for a multi-product, nite horizon, online retail environment. To solve the optimization problem, a myopic pricing heuristic as well as exact solution approaches are introduced. Using customer reviews ratings data from Amazon.com, a new customer rating forecasting model is validated. This is followed by several analytical and numerical insights. In Chapter 4 a multinomial choice model is used for customer purchase decision to find optimal personalized price discounts for an online retailer that incorporates customer locations and feedback from their reviews. Closed form solutions are derived for two special cases of this problem. To gain some analytical insights extensive numerical experiments are carried followed by several analytical and numerical insights. / Thesis / Doctor of Philosophy (PhD) / The increase in online retail and the improvements in mobile technologies has lead to advantages and opportunities for both customers and retailers. One of these advantages is the ability to keep and efficiently access records of historical orders for both customers and retailers. In addition, online retailing has dramatically decreased the cost of price adjustments and discounts compared to the brick and mortar environment. At the same time, with the increase in online retailing we are witnessing proliferations of online reviews in e-commerce platforms. Given this availability of data and the new capabilities in an online retail environment, there is a need to develop pricing optimization models that integrate all these new features. The overarching motivation and theme of this thesis is to review these opportunities and provide methods and models in the context of retailers' online pricing decisions.
115

The Impact of Quantum Computing on the Financial Sector : Exploring the Current Performance and Prospects of Quantum Computing for Financial Applications through Mean-Variance Optimization

Fahlkvist, Ante, Kheiltash, Alfred January 2023 (has links)
Many important tasks in finance often rely on complex and time-consuming computations. The rapid development of quantum technology has raised the question of whether quantum computing can be used to solve these tasks more efficiently than classical computing. This thesis studies the potential use of quantum computing in finance by solving differently-sized problem instances of the mean-variance portfolio selection model using commercially available quantum resources. The experiments employ gate-based quantum computers and quantum annealing, the two main technologies for realizing a quantum computer. To solve the mean-variance optimization problem on gate-based quantum computers, the model was formulated as a quadratic unconstrained binary optimization (QUBO) problem, which was then used as input to quantum resources available on the largest quantum computing as a service (QCaaS) platforms, IBM Quantum Lab, Microsoft Azure Quantum and Amazon Braket. To solve the problem using quantum annealing, a hybrid quantum-classical solver available on the service D-Wave Leap was employed, which takes as input the mean-variance model’s constrained quadratic form. The problem instances were also solved classically on the model’s QUBO form, where the results acted as benchmarks for the performances of the quantum resources. The results were evaluated based on three performance metrics: time-to-solve, solution quality, and cost-to-solve. The findings indicate that gate-based quantum computers are not yet mature enough to consistently find optimal solutions, with the computation times being long and costly as well. Moreover, the use of gate-based quantum computers was not trouble-free, with the majority of quantum computers failing to even complete the jobs. Quantum annealing, on the other hand, demonstrated greater maturity, with the hybrid solver being capable of fast and accurate optimization, even for very large problem instances. The results from using the hybrid solver justify further research into quantum annealing, to better understand the capabilities and limitations of the technology. The results also indicate that quantum annealing has reached a level of maturity where it has the potential to make a significant impact on financial institutions, creating value that cannot be obtained by using classical computing.
116

Performance optimization of engineering systems with particular reference to dry-cooled power plants

Conradie, Antonie Eduard 03 1900 (has links)
Thesis (PhD (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 1995. / Computer simulation programs were developed for the analysis of dry-cooling systems for power plant applications. Both forced draft direct condensing air"cooled condensers and hyperbolic natural draft indirect dry-cooling towers are considered. The results of a considerable amount of theoretical and experimental work are taken into account to model all the physical phenomena ofthese systems, to formu1ate the problems in formal mathematical terms and to design and apply suitable computational algorithms to solve these problems effectively and reliably. The dry-cooling systems are characterized by equation-based models. These equations are simultaneously solved by a specially designed constrained nonlinear least squares algorithm to determine the performance characteristics of the dry-cooling systems under fixed prescnoed operating conditions, or under varying operating conditions when coupled to a turbo-generator set. The solution procedure is very fast and effective. A capital and operating cost estimation procedure, based on information obtained from dry-cooling system component manufacturers and the literature, is proposed. Analytical functions express the annual cost in terms ofthe various geometrical and operating parameters ofthe dry-cooling systems. The simu1ation and the cost estimation procedures were coupled to a constrained nonlinear programming code which enable the design of minimum cost dry-cooling systems at fixed prescribed operating conditions, or dry-cooling systems which minimize the ratio of total annual cost to the annual net power output of the corresponding turbo-generator set. Since prevailing atmospheric conditions, especially the ambient temperature, influence the performance of dry-cooling systems, wide fluctuations in turbine back pressure occur. Therefore, in the latter case the optimal design is based on the annual mean hourly frequency ofambient temperatures, rather than a fixed value. The equation-based models and the optimization problems are simultaneously solved along an infeasible path (infeasible path integrated approach). The optimization model takes into consideration all the parameters that may affect the capital and operating cost of the dry-cooling systems and does not prescribe any limits, other than those absolutely essential due to practical limitations and to simulate the systems effectively. The influence that changes ofthe constraint limits and some problem parameters have on the optinmm solution, are evaluated (sensitivity analysis). The Sequential Quadratic Programming (SQP) method is used as the basis in implementing nonlinear optimization techniques to solve the cost minimirnti~n problems. A stable dual active set algorithm for convex quadratic programming (QP) problems is implemented that makes use of the special features ofthe QP subproblems associated with the SQP methods. TIrls QP algorithm is also used as part of the algorithm that solves the constrained nonlinear least squares problem This particular implementation of the SQP method proved to be very reliable and efficient when applied to the optimization problems based on the infeasible path integrated approach. However, as the nonlinear optimization problems become large, storage requirements for the Hessian matrix and computational expense of solving large quadratic programming (QP) subproblems become prohibitive. To overcome these difficulties, a reduced Hessian SQP decomposition strategy with coordinate bases was implemented. This method exploits the low dimensionality of the subspace of independent decision variables. The performance of this SQP decomposition is further improved by exploiting the mathematical structure of the engineering model, for example the block diagonal structure ofthe Jacobian matrix. Reductions ofbetween 50-90% in the total CPU time are obtained compared to conventional SQP optimization methods. However, more function and gradient evaluations are used by this decomposition strategy. The computer programs were extensively tested on various optimization problems and provide fast and effective means to determine practical trends in the manufacturing and construction of costoptimal dry-cooling systems, as well as their optimal performance and operating conditions in power plant applications. The dissertation shows that, through the proper application of powerful optimization strategies and careful tailoring of the well constructed optimization model, direct optimization of complex models does not need to be time consuming and difficult. Reconnnendations for further research are made. / Imported from http://etd.sun.ac.za April 2010.
117

Integer Quadratic Programming for Control and Communication

Axehill, Daniel January 2008 (has links)
The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control methods is Model Predictive Control (MPC). In each sampling time, MPC requires the solution of a Quadratic Programming (QP) problem. To be able to use MPC for large systems, and at high sampling rates, optimization routines tailored for MPC are used. In recent years, the range of application of MPC has been extended to so-called hybrid systems. Hybrid systems are systems where continuous dynamics interact with logic. When this extension is made, binary variables are introduced in the problem. As a consequence, the QP problem has to be replaced by a far more challenging Mixed Integer Quadratic Programming (MIQP) problem, which is known to have a computational complexity which grows exponentially in the number of binary optimization variables. In modern communication systems, multiple users share a so-called multi-access channel. To estimate the information originally sent, a maximum likelihood problem involving binary variables can be solved. The process of simultaneously estimating the information sent by multiple users is called Multiuser Detection (MUD). In this thesis, the problem to efficiently solve MIQP problems originating from MPC and MUD is addressed. Four different algorithms are presented. First, a polynomial complexity preprocessing algorithm for binary quadratic programming problems is presented. By using the algorithm, some, or all, binary variables can be computed efficiently already in the preprocessing phase. In numerical experiments, the algorithm is applied to unconstrained MPC problems with a mixture of real valued and binary valued control signals, and the result shows that the performance gain can be significant compared to solving the problem using branch and bound. The preprocessing algorithm has also been applied to the MUD problem, where simulations have shown that the bit error rate can be significantly reduced compared to using common suboptimal algorithms. Second, an MIQP algorithm tailored for MPC is presented. The algorithm uses a branch and bound method where the relaxed node problems are solved by a dual active set QP algorithm. In this QP algorithm, the KKT systems are solved using Riccati recursions in order to decrease the computational complexity. Simulation results show that both the proposed QP solver and MIQP solver have lower computational complexity compared to corresponding generic solvers. Third, the dual active set QP algorithm is enhanced using ideas from gradient projection methods. The performance of this enhanced algorithm is shown to be comparable with the existing commercial state-of-the-art QP solver \cplex for some random linear MPC problems. Fourth, an algorithm for efficient computation of the search directions in an SDP solver for a proposed alternative SDP relaxation applicable to MPC problems with binary control signals is presented. The SDP relaxation considered has the potential to give a tighter lower bound on the optimal objective function value compared to the QP relaxation that is traditionally used in branch and bound for these problems, and its computational performance is better than the ordinary SDP relaxation for the problem. Furthermore, the tightness of the different relaxations is investigated both theoretically and in numerical experiments. / This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the Linköping University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this material, you agree to all provisions of the copyright laws protecting it.
118

Formulation of impedance control strategy as an optimal control problem. / Formulação da estratégia do controle de impedância como um problema de controle ótimo.

Guilherme Phillips Furtado 06 September 2018 (has links)
A formulation of impedance control for redundant manipulators is developed as a particular case of an optimal control problem. This formulation allows the planning and design of an impedance controller that benets from the stability and eficiency of an optimal controller. Moreover, to circumvent the high computational costs of computing an optimal controller, a sub-optimal feedback controller based on the state-dependent Ricatti equation (SDRE) approach is developed. This approach is then compared with the quadratic programming (QP) control formulation, commonly used to resolve redundancy of robotic manipulators. Numerical simulations of a redundant planar 4-DOF serial link manipulator show that the SDRE control formulation offers superior performance over the control strategy based QP, in terms of stability, performance and required control effort. / Uma formulação do controle de impedância para manipuladores redundantes é desenvolvida como um caso particular de um problema de controle ótimo. Essa formulação permite o planejamento e projeto de um controlador de impedância que se beneficia da estabilidade e eficiência de um controlador ótimo. Para evitar lidar com os elevados custos computacionais de se computar um controlador ótimo, um controlador em malha fechada sub-ótimo, baseado na abordagem das equações de Ricatti dependentes de estado (SDRE), é desenvolvido. Essa abordagem é comparada com a formulação de um controlador baseado em programação quadrática (QP), usualmente utilizado para resolver problemas de redundância em manipuladores robóticos. Simulações numéricas de um manipulador serial plano de quatro graus de liberdade mostram que o controlador baseado em SDRE oferece performance superior em relação a um controlador baseado em programação quadrática, em termos de estabilidade, performance e esforço de controle requerido do atuador.
119

Formulation of impedance control strategy as an optimal control problem. / Formulação da estratégia do controle de impedância como um problema de controle ótimo.

Furtado, Guilherme Phillips 06 September 2018 (has links)
A formulation of impedance control for redundant manipulators is developed as a particular case of an optimal control problem. This formulation allows the planning and design of an impedance controller that benets from the stability and eficiency of an optimal controller. Moreover, to circumvent the high computational costs of computing an optimal controller, a sub-optimal feedback controller based on the state-dependent Ricatti equation (SDRE) approach is developed. This approach is then compared with the quadratic programming (QP) control formulation, commonly used to resolve redundancy of robotic manipulators. Numerical simulations of a redundant planar 4-DOF serial link manipulator show that the SDRE control formulation offers superior performance over the control strategy based QP, in terms of stability, performance and required control effort. / Uma formulação do controle de impedância para manipuladores redundantes é desenvolvida como um caso particular de um problema de controle ótimo. Essa formulação permite o planejamento e projeto de um controlador de impedância que se beneficia da estabilidade e eficiência de um controlador ótimo. Para evitar lidar com os elevados custos computacionais de se computar um controlador ótimo, um controlador em malha fechada sub-ótimo, baseado na abordagem das equações de Ricatti dependentes de estado (SDRE), é desenvolvido. Essa abordagem é comparada com a formulação de um controlador baseado em programação quadrática (QP), usualmente utilizado para resolver problemas de redundância em manipuladores robóticos. Simulações numéricas de um manipulador serial plano de quatro graus de liberdade mostram que o controlador baseado em SDRE oferece performance superior em relação a um controlador baseado em programação quadrática, em termos de estabilidade, performance e esforço de controle requerido do atuador.
120

Contribution to fault tolerant flight control under actuator failures / Contribution à la commande tolérante aux fautes pour la conduite du vol avec panne d'actionneur

Zhong, Lunlong 27 January 2014 (has links)
L'objectif de cette thèse est d'optimiser l'utilisation d'actionneurs redondants pour un avion de transport lorsqu’une défaillance des actionneurs arrive en vol. La tolérance aux pannes résulte ici de la redondance des actionneurs présents sur l’avion. Différents concepts et méthodes classiques liés aux chaînes de commande de vol tolérantes aux pannes sont d'abord examinés et de nouveaux concepts utiles pour l'analyse requise sont introduits. Le problème qui est abordé ici est de développer une méthode de gestion des pannes des commandes de vol dans le cas d'une défaillance partielle des actionneurs, qui va permettre à l'avion de poursuivre en toute sécurité la manœuvre prévue. Une approche de commande en deux étapes est proposée et appliquée à la fois à l'évaluation de la manoeuvrabilité restante et à la conception de structures de commande tolérante aux pannes. Dans le premier cas, une méthode d'évaluation hors ligne des qualités de vol basée sur la commande prédictive est proposée. Dans le second cas, une structure de commande tolérante aux pannes basée sur la commande non linéaire inverse et la réaffectation des actionneurs en ligne est développée. Dans les deux cas, un problème de programmation linéaire quadratique (LQ) est formulé. Différents cas de pannes sont considérés lorsqu'un avion effectue une manoeuvre classique. Trois solveurs numériques sont appliqués aux solutions en ligne et hors ligne des problèmes LQ qui en résultent. / The objective of this thesis is to optimize the use of redundant actuators for a transportation aircraft once some actuators failure occurs during the flight. Here, the fault tolerant ability resulting from the redundant actuators is mainly considered. Different classical concepts and methods related to a fault tolerant flight control channel are first reviewed and new concepts useful for the required analysis are introduced. The problem which is tackled here is to develop a design methodology for fault tolerant flight control in the case of a partial actuator failure which will allow the aircraft to continue safely the intended maneuver. A two stages control approach is proposed and applied to both the remaining maneuverability evaluation and a fault tolerant control structure design. In the first case, an offline handling qualities assessment method based on Model Predictive Control is proposed. In the second case, a fault tolerant control structure based on Nonlinear Inverse Control and online actuator reassignment is developed. In both cases, a Linear Quadratic (LQ) programming problem is formulated and different failure cases are considered when an aircraft performs a classical maneuver. Three numerical solvers are studied and applied to the offline and online solutions of the resulting LQ problems.

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