A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Physiological indicators of stress in gestating sows under different cooling systems

The objective of this work was to determine physiological stress markers, neutrophil:lymphocyte ratio (N/L) and corticoid concentrations, in gestating sows under different cooling systems. A sprinkling cooling system (SS) and a system based on fan-assisted evaporative cellulose pad (PS) were used. SS showed higher N/L ratio (1.095) than PS (0.850). Corticoid concentrations showed high variability. Corticosteroids are more efficient short-term stress indicators while N/L ratio is a good medium and long-term stress indicator. According to N/L ratio, gestating sows under PS benefit from a higher level of welfare.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

New directions in Stochastic Multicriteria Acceptability Analysis

Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.

Impingement jet cooling of end windings in a high-speed electric machine

The rotational speed of high-speed electric machines is over 15 000 rpm. These machines are compact in size when compared to the power rate. As a consequence, the heat fluxes are at a high level and the adequacy of cooling becomes an important design criterion. In the high-speed machines, the air gap between the stator and rotor is a narrow flow channel. The cooling air is produced with a fan and the flow is then directed to the air gap. The flow in the gap does not provide sufficient cooling for the stator end windings, and therefore additional cooling is required. This study investigates the heat transfer and flow fields around the coil end windings when cooling jets are used. As a result, an innovative and new assembly is introduced for the cooling jets, with the benefits of a reduced amount of hot spots, a lower pressure drop, and hence a lower power need for the cooling fan. The gained information can also be applied to improve the cooling of electric machines through geometry modifications. The objective of the research is to determine the locations of the hot spots and to find out induced pressure losses with different jet alternatives. Several possibilities to arrange the extra cooling are considered. In the suggested approach cooling is provided by using a row of air jets. The air jets have three main tasks: to cool the coils effectively by direct impingement jets, to increase and cool down the flow that enters the coil end space through the air gap, and to ensure the correct distribution of the flow by forming an air curtain with additional jets. One important aim of this study is the arrangement of cooling jets in such manner that hot spots can be avoided to wide extent. This enables higher power density in high-speed motors. This cooling system can also be applied to the ordinary electric machines when efficient cooling is needed. The numerical calculations have been performed using a commercial Computational Fluid Dynamics software. Two geometries have been generated: cylindrical for the studied machine and Cartesian for the experimental model. The main parameters include the positions, arrangements and number of jets, the jet diameters, and the jet velocities. The investigated cases have been tested with two widely used turbulence models and using a computational grid of over 500 000 cells. The experimental tests have been made by using a simplified model for the end winding space with cooling jets. In the experiments, an emphasis has been given to flow visualisation. The computational analysis shows good agreement with the experimental results. Modelling of the cooling jet arrangement enables also a better understanding of the complex system of heat transfer at end winding space.

The impact of a register on the management of neonatal cooling in Switzerland.

BACKGROUND: Therapeutic hypothermia following hypoxic ischaemic encephalopathy in term infants was introduced into Switzerland in 2005. Initial documentation of perinatal and resuscitation details was poor and neuromonitoring insufficient. In 2011, a National Asphyxia and Cooling Register was introduced. AIMS: To compare management of cooled infants before and after introduction of the register concerning documentation, neuromonitoring, cooling methods and evaluation of temperature variability between cooling methods. STUDY DESIGN: Data of cooled infants before the register was in place (first time period: 2005-2010) and afterwards (second time period: 2011-2012) was collected with a case report form. RESULTS: 150 infants were cooled during the first time period and 97 during the second time period. Most infants were cooled passively or passively with gel packs during both time periods (82% in 2005-2010 vs 70% in 2011-2012), however more infants were cooled actively during the second time period (18% versus 30%). Overall there was a significant reduction in temperature variability (p < 0.001) comparing the two time periods. A significantly higher proportion of temperature measurements within target temperature range (72% versus 77%, p < 0.001), fewer temperature measurements above (24% versus 7%, p < 0.001) and more temperatures below target range (4% versus 16%, p < 0.001) were recorded during the second time period. Neuromonitoring improved after introduction of the cooling register. CONCLUSION: Management of infants with HIE improved since introducing the register. Temperature variability was reduced, more temperature measurements in the target range and fewer temperature measurements above target range were observed. Neuromonitoring has improved, however imaging should be performed more often.

Using time and stochastic models for software reliability forecasting and analysis

Tämä työ luo katsauksen ajallisiin ja stokastisiin ohjelmien luotettavuus malleihin sekä tutkii muutamia malleja käytännössä. Työn teoriaosuus sisältää ohjelmien luotettavuuden kuvauksessa ja arvioinnissa käytetyt keskeiset määritelmät ja metriikan sekä varsinaiset mallien kuvaukset. Työssä esitellään kaksi ohjelmien luotettavuusryhmää. Ensimmäinen ryhmä ovat riskiin perustuvat mallit. Toinen ryhmä käsittää virheiden ”kylvöön” ja merkitsevyyteen perustuvat mallit. Työn empiirinen osa sisältää kokeiden kuvaukset ja tulokset. Kokeet suoritettiin käyttämällä kolmea ensimmäiseen ryhmään kuuluvaa mallia: Jelinski-Moranda mallia, ensimmäistä geometrista mallia sekä yksinkertaista eksponenttimallia. Kokeiden tarkoituksena oli tutkia, kuinka syötetyn datan distribuutio vaikuttaa mallien toimivuuteen sekä kuinka herkkiä mallit ovat syötetyn datan määrän muutoksille. Jelinski-Moranda malli osoittautui herkimmäksi distribuutiolle konvergaatio-ongelmien vuoksi, ensimmäinen geometrinen malli herkimmäksi datan määrän muutoksille.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

ABSTRACT The traditional method of net present value (NPV) to analyze the economic profitability of an investment (based on a deterministic approach) does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L.) production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV) were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV) such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in Chile.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Cooling system optimization in medium-speed engines

Tässä työssä optimoidaan keskinopean Wärtsilä 32 -dieselmoottorin jäähdytysjärjestelmää ja tutkitaan taajuusmuuttajien käyttömahdollisuutta kiertopumppujen yhteydessä niin, että järjestelmässä saataisiin kiertämään vain kulloinkin tarvittava määrä vettä. Tutkimuksen mallinnus on toteutettu laatimalla aiemmin käytössä olleista yksinkertaisista simulointimalleista yksi malli, johon on sisällytetty sekä virtauksen että lämmönsiirron laskenta, jotka on aiemmin mallinnettu erillisillä ohjelmilla. Diplomityö on osa projektia, joka on tehty Sähkötekniikan osaston tutkijan Mikko Pääkkösen kanssa yhteistyössä. Tämän diplomityö keskittyy lähinnä virtausteknisiin ja lämmönsiirtoon liittyviin asioihin, kun taas sähkötekniikan osuus on esitetty Mikko Pääkkösen raportissa. Tulosten perustella voidaan sanoa, että taajuusmuuttajakäyttö kannattaa kiertopumppujen yhteydessä. Käyttämällä pumppujen virtaussäätöä voidaan jäähdytysjärjestelmästä jättää monia komponentteja, kuten termostaattiventtiilejä pois. Mallinnetut yksinkertaiset piiriratkaisut näyttävät toimivan ainakin yleisellä tasolla. Tutkimusta pumppujen säädöstä ja tässä projektissa luoduista jäähdytysjärjestelmäkonfiguraatioista kannattaa jatkaa.

Synthesis of highly focused fields with circular polarization at any transverse plane

We develop a method for generating focused vector beams with circular polarization at any transverse plane. Based on the Richards-Wolf vector model, we derive analytical expressions to describe the propagation of these set of beams near the focal area. Since the polarization and the amplitude of the input beam are not uniform, an interferometric system capable of generating spatially-variant polarized beams has to be used. In particular, this wavefront is manipulated by means of spatial light modulators displaying computer generated holograms and subsequently focused using a high numerical aperture objective lens. Experimental results using a NA=0.85 system are provided: irradiance and Stokes images of the focused field at different planes near the focal plane are presented and compared with those obtained by numerical simulation.

Monotonic continuous-time random walks with drift and stochastic reset events

In this paper we consider a stochastic process that may experience random reset events which suddenly bring the system to the starting value and analyze the relevant statistical magnitudes. We focus our attention on monotonic continuous-time random walks with a constant drift: The process increases between the reset events, either by the effect of the random jumps, or by the action of the deterministic drift. As a result of all these combined factors interesting properties emerge, like the existence (for any drift strength) of a stationary transition probability density function, or the faculty of the model to reproduce power-law-like behavior. General formulas for two extreme statistics, the survival probability, and the mean exit time, are also derived. To corroborate in an independent way the results of the paper, Monte Carlo methods were used. These numerical estimations are in full agreement with the analytical predictions.