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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.

Cancer treatment optimization

Cha, Kyungduck. January 2008 (has links)
Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008. / Committee Chair: Lee, Eva K.; Committee Member: Barnes, Earl; Committee Member: Hertel, Nolan E.; Committee Member: Johnson, Ellis; Committee Member: Monteiro, Renato D.C.

Quadratic programming algorithms, anomalies [and] applications.

Boot, John C. G., January 1964 (has links)
Proefschrift--Nederlandsche Economische Hoogeschool, Rotterdam. / "Stellingen": [4] p. inserted.

Quadratic programming algorithms, anomalies [and] applications.

Boot, John C. G., January 1964 (has links)
Proefschrift--Nederlandsche Economische Hoogeschool, Rotterdam. / "Stellingen": [4] p. inserted.

Aerodynamic design applying automatic differentiation and using robust variable fidelity optimization

Takemiya, Tetsushi. January 2008 (has links)
Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Mavris, Dimitri; Committee Member: Alley, Nicholas; Committee Member: Lakshmi, Sankar; Committee Member: Sriram, Rallabhandi; Committee Member: Stephen, Ruffin. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Framework combining static optimization, dynamic scheduling and decision analysis applicable to complex primary HVAC & R systems /

Jiang, Wei. Reddy, Agami T January 2005 (has links)
Thesis (Ph. D.)--Drexel University, 2005. / Includes abstract and vita. Includes bibliographical references (leaves 192-204).

Projected Barzilai-Borwein Method with Infeasible Iterates for Nonnegative Image Deconvolution

Fraser, Kathleen 22 July 2011 (has links)
The Barzilai-Borwein (BB) method for unconstrained optimization has attracted attention for its "chaotic" behaviour and fast convergence on image deconvolution problems. However, images with large areas of darkness, such as those often found in astronomy or microscopy, have been shown to benefit from approaches which impose a nonnegativity constraint on the pixel values. We present a new adaptation of the BB method which enforces a nonnegativity constraint by projecting the solution onto the feasible set, but allows for infeasible iterates between projections. We show that this approach results in faster convergence than the basic Projected Barzilai-Borwein (PBB) method, while achieving better quality images than the unconstrained BB method. We find that the new method also performs comparably to the Gradient Projection-Conjugate Gradient (GPCG) method, and in most test cases achieves a lower restoration error, despite being a much simpler algorithm.

Aggregation in large scale quadratic programming

Foster, David Martin 08 1900 (has links)
No description available.


Vassalos, Michael 01 January 2013 (has links)
Commercial fresh vegetable production is one of the most rewarding and risky farming activities. The price and yield variations throughout the production year, the special characteristics of fresh vegetable produce (i.e. perishability), and the changing consumer demands are some of the factors contributing to the increased uncertainty faced by vegetable producers. This dissertation combined mathematical programming and econometric techniques to: 1) investigate the optimal production and marketing practices under different price distribution information scenarios, risk aversion levels and marketing outlets and 2) examine growers’ preferences as well the effect of risk aversion levels and growers’ risk perception on the choice of marketing contracts. Specifically, the following three modeling approaches were adopted in order to achieve the dissertation objectives: 1) quadratic programming under a mean-variance framework, 2) discrete choice experiments and 3) a combination of quadratic and integer programming embodied in a meanvariance framework. The findings indicate that optimal production practices and the resulting net returns are substantially influenced not only by the choice of marketing channel but also by growers’ risk aversion levels as well as price knowledge. Furthermore, regarding the choice of marketing contracts, the results highlight the existence of heterogeneity in preferences and illustrate the importance of certification cost, in line with the previous literature. Lastly, the findings indicate that risk aversion and risk preferences do not play a significant role in the choice of contractual agreements by farmers.

Intuitive Mission Handling with Automatic Route Re-planning using Model Predictive Control / Intuitiv uppdragshantering med modellbaserad prediktionsreglering för automatisk ruttomplanering

Andersson, Emma January 2012 (has links)
The system for mission handling in the Gripen fighter aircraft, and in its ground supporting system, consists for example of ways to plan mission routes, create mission points and validate performed missions. The system is complex and for example, the number of different mission points used increases due to changing demands and needs. This master thesis presents suggestions for improvements and simplifications for the mission handling system, to make it more intuitive and more friendly to use. As a base for the suggestions, interviews with pilots from Saab, TUJAS and FMV have been conducted, this is to obtain opinions and ideas from those using the system and have deep knowledge about it. Another possible assistance and improvement is to provide the possibility of on-line automatic re-planning of the mission route in case of obstacles. MPC (Model Predictive Control) has been used to estimate the obstacle’s flight path,and calculate a new route to the next mission point which does not conflict with the estimated enemy’s path. This system has been implemented in Matlab and the concept is demonstrated with different test scenarios where the design parameters (prediction horizon and penalty in the cost function) for the controller are varied, and stationary and moving obstacles are induced. / Systemet för uppdragshantering i stridsflygplanet Gripen, och i dess markstödsystem, består bland annat av uppdragsplanering, skapande av uppdragspunkter och möjligheter att validera utförda uppdrag. Systemet är komplext och exempelvis växer antalet uppdragspunkter med omvärldens ökande krav och behov. Detta examensarbete presenterar förslag till förenklingar och förbättringar i uppdragshanteringssystemet, för att göra det mer intuitivt och användarvänligt. Som grund för förslagen har intervjuer med piloter från Saab, TUJAS och FMV gjorts, för att samla in åsikter och idéer från de som använder systemet och har bred kunskap om det. En förbättring är en möjlighet till online automatisk omplanering av uppdragsrutten vid hinder. MPC (modellbaserad prediktionsreglering) har använts för att estimera den dynamiska fiendens flygväg, och beräkna en ny rutt till nästa uppdragspunkt som inte ligger i konflikt med den estimerade vägen för hindret. Detta system har implementerats i Matlab och konceptet demonstreras med olika testscenarion där prestandaparametrar (prediktionshorisont och straff i kostnadsfunktionen) för regulatorn varieras, och stationära och rörliga hinder induceras.

Neural Network Based Cogeneration Dispatch nder Deregulation

Chou, Yu-ching 03 August 2005 (has links)
Co-generation is an efficient energy system that generates steam and electricity simultaneously. In ordinary operation, fuel cost accounts for more than 60% of the operational cost. As a result, the boiler efficiency and optimization level of co-generation are both high. To achieve further energy conservation, objectives of this thesis are to find the Profit-maximizing dispatch and efficiency enhancing strategy of the co-generation systems under deregulation. In a coexistent environment of both Bilateral and Poolco-based power market, there are bid-based spot dispatch, and purchases and sales agreement-based contract dispatch. For profit-maximizing dispatch, the steam of boilers, fuels and generation output will be obtained by using the SQP(Sequential Quadratic Programming ) method. In order to improve the boiler efficiency, this thesis utilizes artificial neural networks(ANN) and evolutionary programming(EP) methods to search for the optimal operating conditions of boilers. A co-generation system (back-pressure type and extraction type) is used to illustrate the effectiveness of the proposed method.

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