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Diplomová práce měla za úkol aplikovat vybrané metody managementu kvality a tím zanalyzovat údaje o neshodné výrobě odštěpného závodu společnosti Lamela Electric, a.s. Výsledkem analýzy je zjištění příčin vzniku neshod a návrh opatření pro minimalizaci neshodné výroby.

Diplomová práce je zaměřena na významnou italskou osobnost, Maffeo Pantaleoni, a na jeho velký vklad do italské a světové ekonomie. V práci jsou také popsané dva z mnohých problémů, kterými se zabýval italský ekonom na konci 19. a na počátku 20. století; jeho přátelství s Vilfredem Paretem a o skandálu Římské banky, ve kterém Pantaleoni hrál jednu z hlavních rolí. Maffeo Pantaleoni zdůrazňuje důležitost výchozích a konečných pozic pro ekonomické subjekty v díle Výchozí a konečná pozice. Kde ekonom analyzuje a snaží se aplikovat vzájemné působení výchozích a konečných bodů krátkodobých a dlouhodobých časových intervalů v ekonomickém aspektu pomocí příkladů a alegorie. Pomocí druhého díla Některé fenomény ekonomické dynamiky Maffeo Pantaleoni pokračuje ve studiu ekonomů neoklasiků, kteří přesně definovali pojem statiky, a uvádí a vysvětluje dynamiku druhého druhu. Tady autor klade důraz hlavně na vliv rostoucí poptávky na dimenzi podniku a na rozdělení hlavních a specifických výdajů. V obou případech Maffeo Pantaleoni je proti státnímu zásahu a vystupuje pro "svobodnou" ekonomii.

Wildfires in the United States present a complexity of problems for private landowners and policy makers. This thesis takes a look at two key issues faced by private and government stakeholders; the first being a lack of knowledge regarding current prescribed fire laws and regulations. A legal review of administrative laws and regulations for prescribed burning in the Southeastern United States in the context of management-based regulation is used to address this issue. It was found that regulation for prescribed burning has shifted to a more management–based regime. The second is an empirical study of wildfire distribution in the state of Mississippi. Wildfires appear to fit a Pareto distribution throughout the state given a certain threshold. When analyzed in conjunction both studies could aid lawmakers in projecting the effects of a given policy change on actual wildfire occurrences and distribution.

'Climate change is the greatest and widest-ranging market failure ever seen' Stern (2006 p. xvii). This vigorous description highlights one of the most important and frustrating realizations of the last decades. The main reason of that market failure stems from the fact that climate change is a complex global externality. This makes the design of appropriate measures to mitigate the problem and the identification of their effects on economic activity of paramount importance. The transboundary nature of pollution combined with the skewed distribution of the origin and impact of emissions among countries reveals the need for international cooperation in the direction of multilateral agreements among countries. The characterization of Pareto-efficient environmental and trade policies has been a key issue (and continues to be) in the literature. Predominantly, however, the literature has focused on the role of taxes (trade and pollution) in achieving the first-best paying no attention to the role (if there is any) of non-tradeable goods. Chapter 4 deals with this issue. A key issue in mitigating climate change is with the appropriate extent of harmonization of environmental policies. This thesis (Chapters 2) addresses this within a general equilibrium model of international trade with endogenous pollution discharges, paying particular attention to the allocation of tax revenues. It argues that there indeed exist instances in which pollution tax harmonization (that moves the initial pollution taxes towards an appropriately weighted pollution tax vector) can deliver potential Pareto improvements. The difficulty with the achievement of global environmental agreements should not be, however, ignored. Chapter 3 deals with the possibility that governments may act unilaterally in order to mitigate the social cost of pollution. It shows that (under certain conditions) there exist unilateral Pareto improving trade policy reforms. Chapter 5 discusses the welfare implication of environmental policy reforms within a subset of countries. It shows that environmental policy coordination has opposing effect on the welfare of the coordinating and non-coordinating countries.

O presente trabalho propõe a utilização do método de otimização baseado no paradigma de enxame de partículas no projeto de um dispositivo eletromagnético, modelado analiticamente. A otimização baseada em enxames de partículas pertence à classe dos algoritmos evolutivos e é baseada no algoritmo de simulação do movimento de pássaros na busca por comida. O trabalho será focado na resolução de problemas de otimização multiobjetivo e apenas alguns casos de otimização mono-objetivo serão resolvidos para demonstrar a funcionalidade do método de otimização. Dois métodos de otimização multiobjetivo são propostos: um é baseado num algoritmo de otimização multiobjetivo que utiliza o paradigma de enxames em conjunto com soluções adotadas pelo algoritmo genético multiobjetivo denominado Nondominated Sorting Genetic Algorithm-II (NSGA-II) e o outro é baseado também no paradigma de enxames utilizando elementos do algoritmo de otimização multiobjetivo intitulado Strength Pareto Evolutionary Algorithm (SPEA). Ambos algoritmos são validados em um problema de otimização baseado no projeto de um motor de corrente contínua sem escovas, um benchmark de otimização. / This work proposes the use of the optimization method based on the particle swarm paradigm in the design of electromagnetic device, analytically modeled. Particle swarm optimization belongs to the class of evolutionary algorithms and is based on the movement simulation of birds searching for food. This work will be focused on solving multi-criteria optimization problems and some cases of single-objective optimization problems will be solved only to demonstrate the functionality of optimization method. Two multi-criteria optimization methods are proposed: one based on an optimization algorithm that uses the multiobjective particle swarm paradigm and some concepts extracted from the multiobjective genetic algorithm called Nondominated Sorting Genetic Algorithm-II (NSGA-II) and the other is based on the particle swarm paradigm by using some elements of another multiobjective optimization algorithm entitled Strength Pareto Evolutionary Algorithm (SPEA). Both methods are applied to an optimization problem related to the design of a brushless direct current motor.

O presente trabalho propõe a utilização do método de otimização baseado no paradigma de enxame de partículas no projeto de um dispositivo eletromagnético, modelado analiticamente. A otimização baseada em enxames de partículas pertence à classe dos algoritmos evolutivos e é baseada no algoritmo de simulação do movimento de pássaros na busca por comida. O trabalho será focado na resolução de problemas de otimização multiobjetivo e apenas alguns casos de otimização mono-objetivo serão resolvidos para demonstrar a funcionalidade do método de otimização. Dois métodos de otimização multiobjetivo são propostos: um é baseado num algoritmo de otimização multiobjetivo que utiliza o paradigma de enxames em conjunto com soluções adotadas pelo algoritmo genético multiobjetivo denominado Nondominated Sorting Genetic Algorithm-II (NSGA-II) e o outro é baseado também no paradigma de enxames utilizando elementos do algoritmo de otimização multiobjetivo intitulado Strength Pareto Evolutionary Algorithm (SPEA). Ambos algoritmos são validados em um problema de otimização baseado no projeto de um motor de corrente contínua sem escovas, um benchmark de otimização. / This work proposes the use of the optimization method based on the particle swarm paradigm in the design of electromagnetic device, analytically modeled. Particle swarm optimization belongs to the class of evolutionary algorithms and is based on the movement simulation of birds searching for food. This work will be focused on solving multi-criteria optimization problems and some cases of single-objective optimization problems will be solved only to demonstrate the functionality of optimization method. Two multi-criteria optimization methods are proposed: one based on an optimization algorithm that uses the multiobjective particle swarm paradigm and some concepts extracted from the multiobjective genetic algorithm called Nondominated Sorting Genetic Algorithm-II (NSGA-II) and the other is based on the particle swarm paradigm by using some elements of another multiobjective optimization algorithm entitled Strength Pareto Evolutionary Algorithm (SPEA). Both methods are applied to an optimization problem related to the design of a brushless direct current motor.

Darbe nagrinėjami vienmačių nepriklausomų dydžių tiesiškai normuotų maksimumų skirstinių konvergavimo greičiai perkėlimo teoremoje. Tiriami du atvejai: • konvergavimo greičio įvertis, kai dydžių skirstiniai yra maks – stabilūs; • įverčiai, kai atsitiktiniai dydžiai yra apibendrintieji Pareto. Nagrinėjami netolygieji konvergavimo greičio įverčiai, kai nepriklausomų atsitiktinių dydžių skaičius pasiskirstęs pagal geometrinį arba diskretųjį tolygųjį skirstinį. Taip pat randamos tiksliosios absoliučiosios paklaidos pastarųjų skirstinių atveju. Atliekama kompiuterinė konvergavimo greičių įverčių ir absoliučiųjų paklaidų palyginamoji analizė. Tyrimo rezultatai patikslina A. Aksomaičio (1999) ir Gnedenkos (1982) darbų teiginius. / Asymptotics of maxima of independent and identically distributed random variables (i. i. d.) is presented in the paper. We will research the cases when the distributions are max – stable, distributions are generalized Pareto and the size of set of independent random variables is random. The non – uniform and uniform estimates of the rate of convergence for transfer theorem are obtained in this scheme. These estimations improve the result given in A. Aksomaitis (1999) and Gnedenko (1982).

Darbo tikslas – sukonstruoti dvimatį skirstinį, kai duoti vienmačiai (marginalieji) skirstiniai, atlikti maksimumų asimptotinę analizę ir ištirti konvergavimo greitį. Dvimatis skirstinys konstruojamas dviem atvejais: kai vektorių komponentės yra priklausomos ir nepriklausomos. Detalesnė konvergavimo greičio analizė atlikta, kai komponentės yra priklausomos. Tyrimui buvo pasirinktas Pareto skirstinys. Pirmoje tiriamosios dalies ir rezultatų dalyje yra konstruojamas dvimatis skirstinys, skaičiuojamos jo pagrindinės charakteristikos, tiriama, ar prie visų parametrų reikšmių jos egzistuoja. Taip pat generuojami atsitiktiniai dydžiai, kurių skirstiniai yra sukonstruotosios skirstinio funkcijos marginalieji skirstiniai, ir eksperimentiškai bandoma pagrįsti gautus rezultatus. Antroje dalyje atliekama asimptotinė analizė. Apibrėžiami dvimačiai maksimumai, ieškomas ribinis skirstinys. Juos suradus, apibrėžiamas apytikslis konvergavimo greičio įvertis, atliekama jo bei paklaidų kompiuterinė analizė, ieškoma, kokioms sąlygoms esant jie yra mažiausi. Sukonstruoto dvimačio skirstinio skaitinių charakteristikų tyrimas atliekama programiniu paketu MathCAD. Kompiuterinė konvergavimo greičio įverčių analizė atliekama programinio paketo Matlab pagalba. Jo aplinkoje buvo sukurta programa vartotojui, kuri nubraižo konvergavimo greičio įvertį bei paklaidas. / The aim of this paper is to construct two-dimensional random variables, having one-dimensional ones, carry out the asymptotical analysis and study the speed of convergence. Two-dimensional distribution is constructed in two ways: when the components of random variables are independent and dependent. As in the last few years Pareto distribution is popular in financial models, it was chosen for the analyses. It was proved, that in both cases of independent and dependent components of the vector, the limit distribution is the same. This means that although the components of the vector are dependent, the maxima are asymptotically independent. Besides, the errors are smaller than the approximate estimate. Although, the approximate estimate in the case of independent components is smaller than in the case of dependent components, the errors are on the contrary: they are smaller when the components are dependent than when the components are independent.

We study the two-user multiple-input single-output (MISO) Gaussian interference channel where the transmitters have perfect channel state information and employ single-stream beamforming. The receivers are capable of performing successive interference cancellation, so when the interfering signal is strong enough, it can be decoded, treating the desired signal as noise, and subtracted from the received signal, before the desired signal is decoded. We propose efficient methods to compute the Pareto-optimal rate points and corresponding beamforming vector pairs, by maximizing the rate of one link given the rate of the other link. We do so by splitting the original problem into four subproblems corresponding to the combinations of the receivers' decoding strategies - either decode the interference or treat it as additive noise. We utilize recently proposed parameterizations of the optimal beamforming vectors to equivalently reformulate each subproblem as a quasi-concave problem, which we solve very efficiently either analytically or via scalar numerical optimization. The computational complexity of the proposed methods is several orders-of-magnitude less than the complexity of the state-of-the-art methods. We use the proposed methods to illustrate the effect of the strength and spatial correlation of the channels on the shape of the rate region.