On the use of convex underestimators in global optimization

Många kvantitativa problem från vitt skilda områden kan beskrivas som optimeringsproblem. Ett mått på lösningens kvalitet bör optimeras samtidigt som vissa villkor på lösningen uppfylls. Kvalitetsmåttet kallas vanligen objektfunktion och kan beskriva kostnader (exempelvis produktion, logistik), potentialenergi (molekylmodellering, proteinveckning), risk (finans, försäkring) eller något annat relevant mått. I min doktorsavhandling diskuteras speciellt icke-linjär programmering, NLP, i ändliga dimensioner. Problem med enkel struktur, till exempel någon form av konvexitet, kan lösas effektivt. Tyvärr kan inte alla kvantitativa samband modelleras på ett konvext vis. Icke-konvexa problem kan angripas med heuristiska metoder, algoritmer som söker lösningar med hjälp av deterministiska eller stokastiska tumregler. Ibland fungerar det här väl, men heuristikerna kan sällan garantera kvaliteten på lösningen eller ens att en lösning påträffas. För vissa tillämpningar är det här oacceptabelt. Istället kan man tillämpa så kallad global optimering. Genom att successivt dela variabeldomänen i mindre delar och beräkna starkare gränser på det optimala värdet hittas en lösning inom feltoleransen. Den här metoden kallas branch-and-bound, ungefär dela-och-begränsa. För att ge undre gränser (vid minimering) approximeras problemet med enklare problem, till exempel konvexa, som kan lösas effektivt. I avhandlingen studeras tillvägagångssätt för att approximera differentierbara funktioner med konvexa underskattningar, speciellt den så kallade alphaBB-metoden. Denna metod adderar störningar av en viss form och garanterar konvexitet genom att sätta villkor på den perturberade Hessematrisen. Min forskning har lyft fram en naturlig utvidgning av de perturbationer som används i alphaBB. Nya metoder för att bestämma underskattningsparametrar har beskrivits och jämförts. I sammanfattningsdelen diskuteras global optimering ur bredare perspektiv på optimering och beräkningsalgoritmer.

Optimization and validation of the solid-liquid extraction technique for determination of picloram in soils by high performance liquid chromatography

The objective of this study was to optimize and validate the solid-liquid extraction (ESL) technique for determination of picloram residues in soil samples. At the optimization stage, the optimal conditions for extraction of soil samples were determined using univariate analysis. Ratio soil/solution extraction, type and time of agitation, ionic strength and pH of extraction solution were evaluated. Based on the optimized parameters, the following method of extraction and analysis of picloram was developed: weigh 2.00 g of soil dried and sieved through a sieve mesh of 2.0 mm pore, add 20.0 mL of KCl concentration of 0.5 mol L-1, shake the bottle in the vortex for 10 seconds to form suspension and adjust to pH 7.00, with alkaline KOH 0.1 mol L-1. Homogenate the system in a shaker system for 60 minutes and then let it stand for 10 minutes. The bottles are centrifuged for 10 minutes at 3,500 rpm. After the settlement of the soil particles and cleaning of the supernatant extract, an aliquot is withdrawn and analyzed by high performance liquid chromatography. The optimized method was validated by determining the selectivity, linearity, detection and quantification limits, precision and accuracy. The ESL methodology was efficient for analysis of residues of the pesticides studied, with percentages of recovery above 90%. The limits of detection and quantification were 20.0 and 66.0 mg kg-1 soil for the PVA, and 40.0 and 132.0 mg kg-1 soil for the VLA. The coefficients of variation (CV) were equal to 2.32 and 2.69 for PVA and TH soils, respectively. The methodology resulted in low organic solvent consumption and cleaner extracts, as well as no purification steps for chromatographic analysis were required. The parameters evaluated in the validation process indicated that the ESL methodology is efficient for the extraction of picloram residues in soils, with low limits of detection and quantification.

Currency Carry Trades – Excess Returns and Performance Optimization of G10 Currency Carry Trade Strategies during the Euro Era

This study examines the excess returns provided by G10 currency carry trading during the Euro era. The currency carry trade has been a popular trade throughout the past decades offering excess returns to investors. The thesis aims to contribute to existing research on the topic by utilizing a new set of data for the Euro era as well as using the Euro as a basis for the study. The focus of the thesis is specifically on different carry trade strategies’ performance, risk and diversification benefits. The study finds proof of the failure of the uncovered interest rate parity theory through multiple regression analyses. Furthermore, the research finds evidence of significant diversification benefits in terms of Sharpe ratio and improved return distributions. The results suggest that currency carry trades have offered excess returns during 1999-2014 and that volatility plays an important role in carry trade returns. The risk, however, is diversifiable and therefore our results support previous quantitative research findings on the topic.

Tukin mittaus ja optimointi sahalinjassa

Tukin mittaus ennen sahausta ja sahausasetteen optimointi on kehittynyt paljon viimeisen 10 vuoden aikana. Sahauksen kannattavuuden huonontuessa raaka-aineen tehokas hyödyntäminen on muodostunut tärkeäksi osaksi prosessia. Mittalaitteiden tekniikan kehityttyä on ollut mahdollista mitata tukin muoto ja halkaisijat eri kohdista entistä tarkemmin. Sahausasetteen optimoinnilla pyritään raaka-aineen mahdollisimman tehokkaaseen käyttöön eli saamaan mahdollisimman hyvä saanto jokaisesta yksittäisestä sahatusta tukista. Mittaustarkkuus on suoraan kytköksissä sahausasetteen optimointi tuloksen onnistumiseen. Yleisesti tukin mittaus ennen sahausta ja sahausasetteen optimointi tulevat samalta toimittajalta. Työssä tarkasteltiin kahden eri toimittajan tukkimittareita sekä optimoinnin onnistumista sen perusteella. Käytössä oli lasikuituinen mallitukki, jota mitattiin kummankin toimittajan mittareilla. Näin voitiin suoraan vertailla mittauksen ja optimoinnin onnistumista ja verrata sitä optimaalisiin tuloksiin. Työssä käytettiin kandidaatintyössä luomaani toimintamallia tukkimittarin tarkkuuden toteamiseksi. Mittaus- ja optimointivirheistä pystyttiin laskemaan, kuinka paljon tappiota sahalaitokselle aiheutui verrattuna optimaaliseen mittaus- ja optimointitulokseen. Jo pienetkin virheet optimoinnissa ja mittauksessa vaikuttavat sahauksen kannattavuuteen, kun tarkastellaan sahalaitosta jossa sahataan 8000 – 10 000 tukkia yhden työvuoron aikana. Tulosten perusteella mittarit mittaavat hieman virheellisesti, ja kummankin mittarin mittausten perusteella saatiin eri sahausasete optimointitulokseksi. Mittavirheen takia voitiin todeta, että parantamalla mittaustarkkuutta voidaan sahauksen kannattavuutta parantaa.

Production planning and optimization of a pulp mill: introduction of the optimisation based scheduling software for pulp industry

The objective of this project was to introduce a new software product to pulp industry, a new market for case company. An optimization based scheduling tool has been developed to allow pulp operations to better control their production processes and improve both production efficiency and stability. Both the work here and earlier research indicates that there is a potential for savings around 1-5%. All the supporting data is available today coming from distributed control systems, data historians and other existing sources. The pulp mill model together with the scheduler, allows what-if analyses of the impacts and timely feasibility of various external actions such as planned maintenance of any particular mill operation. The visibility gained from the model proves also to be a real benefit. The aim is to satisfy demand and gain extra profit, while achieving the required customer service level. Research effort has been put both in understanding the minimum features needed to satisfy the scheduling requirements in the industry and the overall existence of the market. A qualitative study was constructed to both identify competitive situation and the requirements vs. gaps on the market. It becomes clear that there is no such system on the marketplace today and also that there is room to improve target market overall process efficiency through such planning tool. This thesis also provides better overall understanding of the different processes in this particular industry for the case company.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Distribution network design and optimization

The objective of this thesis is to examine distribution network designs and modeling practices and create a framework to identify best possible distribution network structure for the case company. The main research question therefore is: How to optimize case company’s distribution network in terms of customer needs and costs? Theory chapters introduce the basic building blocks of the distribution network design and needed calculation methods and models. Framework for the distribution network projects was created based on the theory and the case study was carried out by following the defined framework. Distribution network calculations were based on the company’s sales plan for the years 2014 - 2020. Main conclusions and recommendations were that the new Asian business strategy requires high investments in logistics and the first step is to open new satellite DC in China as soon as possible to support sales and second possible step is to open regional DC in Asia within 2 - 4 years.

Medical applications of shape memory alloys

Shape memory alloys (SMA) are materials that have the ability to return to a former shape when subjected to an appropriate thermomechanical procedure. Pseudoelastic and shape memory effects are some of the behaviors presented by these alloys. The unique properties concerning these alloys have encouraged many investigators to look for applications of SMA in different fields of human knowledge. The purpose of this review article is to present a brief discussion of the thermomechanical behavior of SMA and to describe their most promising applications in the biomedical area. These include cardiovascular and orthopedic uses, and surgical instruments.

Conical aluminum can

The current beverage (cylindrical shape) cans are stacked on each other after production, thus consuming a lot of space. Indirectly, this could result to high carbon emission during transportation. The problem is how to minimize the carbon emission based on different contradicting viewpoints. It was suggested that a conical shape of "the beverage can" could be a solution for the space optimization of empty beverage can transportation, thus creating the title for this research “Conical aluminum can”. They would be stacked inside each other before filling. This was based on design for sustainability and the consumer perspective and willingness toward sustainability. However, it was noticed that the industry is unwilling to incorporate this change.

Changes in cell shape, cytoskeletal proteins and adhesion sites of cultured cells after extracellular Ca2+ chelation

Although much is known about the molecules involved in extracellular Ca2+ regulation, the relationship of the ion with overall cell morphology is not understood. The objective of the present study was to determine the effect of the Ca2+ chelator EGTA on the major cytoskeleton components, at integrin-containing adhesion sites, and their consequences on cell shape. Control mouse cell line C2C12 has a well-spread morphology with long stress fibers running in many different directions, as detected by fluorescence microscopy using rhodamine-phalloidin. In contrast, cells treated with EGTA (1.75 mM in culture medium) for 24 h became bipolar and showed less stress fibers running in one major direction. The adhesion plaque protein alpha5-integrin was detected by immunofluorescence microscopy at fibrillar adhesion sites in both control and treated cells, whereas a dense labeling was seen only inside treated cells. Microtubules shifted from a radial arrangement in control cells to a longitudinal distribution in EGTA-treated cells, as analyzed by immunofluorescence microscopy. Desmin intermediate filaments were detected by immunofluorescence microscopy in a fragmented network dispersed within the entire cytoplasm in EGTA-treated cells, whereas a dense network was seen in the whole cytoplasm of control cells. The present results suggest that the role of extracellular Ca2+ in the regulation of C2C12 cell shape can be mediated by actin-containing stress fibers and microtubules and by intermediate filament reorganization, which may involve integrin adhesion sites.

Stability Analysis in Multicriteria Discrete Portfolio Optimization.

Almost every problem of design, planning and management in the technical and organizational systems has several conflicting goals or interests. Nowadays, multicriteria decision models represent a rapidly developing area of operation research. While solving practical optimization problems, it is necessary to take into account various kinds of uncertainty due to lack of data, inadequacy of mathematical models to real-time processes, calculation errors, etc. In practice, this uncertainty usually leads to undesirable outcomes where the solutions are very sensitive to any changes in the input parameters. An example is the investment managing. Stability analysis of multicriteria discrete optimization problems investigates how the found solutions behave in response to changes in the initial data (input parameters). This thesis is devoted to the stability analysis in the problem of selecting investment project portfolios, which are optimized by considering different types of risk and efficiency of the investment projects. The stability analysis is carried out in two approaches: qualitative and quantitative. The qualitative approach describes the behavior of solutions in conditions with small perturbations in the initial data. The stability of solutions is defined in terms of existence a neighborhood in the initial data space. Any perturbed problem from this neighborhood has stability with respect to the set of efficient solutions of the initial problem. The other approach in the stability analysis studies quantitative measures such as stability radius. This approach gives information about the limits of perturbations in the input parameters, which do not lead to changes in the set of efficient solutions. In present thesis several results were obtained including attainable bounds for the stability radii of Pareto optimal and lexicographically optimal portfolios of the investment problem with Savage's, Wald's criteria and criteria of extreme optimism. In addition, special classes of the problem when the stability radii are expressed by the formulae were indicated. Investigations were completed using different combinations of Chebyshev's, Manhattan and Hölder's metrics, which allowed monitoring input parameters perturbations differently.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Changes in cell shape and desmin intermediate filament distribution are associated with down-regulation of desmin expression in C2C12 myoblasts grown in the absence of extracellular Ca2+

Desmin is the main intermediate filament (IF) protein of muscle cells. In skeletal muscle, desmin IFs form a scaffold that interconnects the entire contractile apparatus with the subsarcolemmal cytoskeleton and cytoplasmic organelles. The interaction between desmin and the sarcolemma is mediated by a number of membrane proteins, many of which are Ca2+-sensitive. In the present study, we analyzed the effects of the Ca2+ chelator EGTA (1.75 mM) on the expression and distribution of desmin in C2C12 myoblasts grown in culture. We used indirect immunofluorescence microscopy and reverse transcription polymerase chain reaction (RT-PCR) to analyze desmin distribution and expression in C2C12 cells grown in the presence or absence of EGTA. Control C2C12 myoblasts showed a well-spread morphology after a few hours in culture and became bipolar when grown for 24 h in the presence of EGTA. Control C2C12 cells showed a dense network of desmin from the perinuclear region to the cell periphery, whereas EGTA-treated cells showed desmin aggregates in the cytoplasm. RT-PCR analysis revealed a down-regulation of desmin expression in EGTA-treated C2C12 cells compared to untreated cells. The present results suggest that extracellular Ca2+ availability plays a role in the regulation of desmin expression and in the spatial distribution of desmin IFs in myoblasts, and is involved in the generation and maintenance of myoblast cell shape.

Optimization of a dynamic district heating power plant

The purpose of this Thesis is to find the most optimal heat recovery solution for Wärtsilä’s dynamic district heating power plant considering Germany energy markets as in Germany government pays subsidies for CHP plants in order to increase its share of domestic power production to 25 % by 2020. Different heat recovery connections have been simulated dozens to be able to determine the most efficient heat recovery connections. The purpose is also to study feasibility of different heat recovery connections in the dynamic district heating power plant in the Germany markets thus taking into consideration the day ahead electricity prices, district heating network temperatures and CHP subsidies accordingly. The auxiliary cooling, dynamical operation and cost efficiency of the power plant is also investigated.

Facilitatory effects of an auditory warning stimulus in a visual location identification task and a visual shape identification task

The occurrence of a weak auditory warning stimulus increases the speed of the response to a subsequent visual target stimulus that must be identified. This facilitatory effect has been attributed to the temporal expectancy automatically induced by the warning stimulus. It has not been determined whether this results from a modulation of the stimulus identification process, the response selection process or both. The present study examined these possibilities. A group of 12 young adults performed a reaction time location identification task and another group of 12 young adults performed a reaction time shape identification task. A visual target stimulus was presented 1850 to 2350 ms plus a fixed interval (50, 100, 200, 400, 800, or 1600 ms, depending on the block) after the appearance of a fixation point, on its left or right side, above or below a virtual horizontal line passing through it. In half of the trials, a weak auditory warning stimulus (S1) appeared 50, 100, 200, 400, 800, or 1600 ms (according to the block) before the target stimulus (S2). Twelve trials were run for each condition. The S1 produced a facilitatory effect for the 200, 400, 800, and 1600 ms stimulus onset asynchronies (SOA) in the case of the side stimulus-response (S-R) corresponding condition, and for the 100 and 400 ms SOA in the case of the side S-R non-corresponding condition. Since these two conditions differ mainly by their response selection requirements, it is reasonable to conclude that automatic temporal expectancy influences the response selection process.