Analysis, design, optimization and realization of compact high performance printed RF filters

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Design optimization of savonius and wells turbines

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2011

Polyhedral and combinatorial aspects in optimization

Magdeburg, Univ., Fak. für Mathematik, Habil.-Schr., 2012

Optimization-based solutions to constrained trajectory-tracking and path-following problems

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2012

Algorithmic assistance to the optimization process in vehicle routing problems

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2013

Flow design optimization of blood pumps considering hemolysis

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2015

Robot trajectory optimization for relaxed effective tasks

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Sizes of linear descriptions in combinatorial optimization

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Univ., Dissertation, 2015

Evaluación de fondos de inversión garantizados por medio de portfolio insurance

La elaboración de un índice de performance para la evaluación de carteras de inversión tiene como base la correcta definición de la medida de riesgo a emplear. Este trabajo tiene como objetivo proponer una medida de performance adecuada a la evaluación de carteras de fondos de inversión garantizados. Las particularidades de este tipo de fondos hacen necesario definir una medida explicativa de las características especificas de riesgo de este tipo de carteras. Partiendo de la estrategia de porfolio insurance se define una nueva medida de riesgo basada en el downside risk. Proponemos como medida de downside risk aquella parte del riesgo total de una cartera de títulos que se elimina con la estrategia de portfolio insurance. Por contraposición, proponemos como medida de upside risk aquella otra parte del riesgo total de la cartera que no desaparece con la estrategia de portfolio insurance. De este modo, la suma del upside risk y del downside risk es el riesgo total. Partiendo de la medida de riesgo upside risk y del modelo de valoración de activos C.A.P.M. se propone una medida de performance específica para evaluar los fondos de inversión garantizados.

Single period Markowitz portfolio selection, performance gauging and duality: a variation on Luenberger's shortage function

Markowitz portfolio theory (1952) has induced research into the efficiency of portfolio management. This paper studies existing nonparametric efficiency measurement approaches for single period portfolio selection from a theoretical perspective and generalises currently used efficiency measures into the full mean-variance space. Therefore, we introduce the efficiency improvement possibility function (a variation on the shortage function), study its axiomatic properties in the context of Markowitz efficient frontier, and establish a link to the indirect mean-variance utility function. This framework allows distinguishing between portfolio efficiency and allocative efficiency. Furthermore, it permits retrieving information about the revealed risk aversion of investors. The efficiency improvement possibility function thus provides a more general framework for gauging the efficiency of portfolio management using nonparametric frontier envelopment methods based on quadratic optimisation.

Unconstrained optimization with MINTOOLKIT for GNU octave

The paper documents MINTOOLKIT for GNU Octave. MINTOOLKIT provides functions for minimization and numeric differentiation. The main algorithms are BFGS, LBFGS, and simulated annealing. Examples are given.

Clean Development Mechanism and Sustainable Development: a discussion on the link between the CDM and Sustainable Development, an analysis of the current status of the CDM portfolio, and an multicriteria evaluation of the effects of additional incentives in order to foster broad local Sustainable Development dividends from the CDM projects

vegeu resum en el fitxer adjunt a l'inici del treball de recerca

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Three essays on the psychology of investment and financial markets

Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

A musculoskeletal shoulder model based on pseudo-inverse and null-space optimization.

The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.