Logistics Development in Finnish and Swedish Companies with Respect of Russia and Four Asian Countries: Traffic Flow and Warehousing Analysis from Current Situation and Likely Development Trends

On selvää, että tänä päivänä maailmankaupan painopiste on hiljalleen siirtymässä Aasiaan ja varsinkin Kiina on ollut huomion keskipisteessä. Erityisesti valmistavien yritysten perspektiivistä muutos on ollut merkittävä ja tämä tosiasia kasvattaa yrityksissä paineita luoda kustannustehokkaita toimitusketjuratkaisuja,joiden vasteaika on mahdollisimman lyhyt. Samaan aikaan kun tarkastellaan kuljetusvirtoja, huomattaan että maanosien välillä on suuri epätasapaino. Tämä on enimmäkseen seurausta suurten globaalisti toimivien yritysten toimitusketjustrategioista. Useimmat näistä toimijoista optimoivat verkostonsa turvautumalla 'paikalliseen hankintaan', jotta he voisivat paremmin hallita toimitusketjujaan ja saada näitä reagointiherkimmiksi. Valmistusyksiköillä onkin monesti Euroopassa pakko käyttää kalliita raaka-aineita ja puolivalmisteita. Kriittisiksi tekijöiksi osoittautuvat kuljetus- ja varastointikustannukset sekä näiden seurauksena hukka-aika, joka aiheutuu viivästyksistä. Voidakseen saavuttaa optimiratkaisun, on tehtävä päätös miten tuotteet varastoidaan: keskitetysti tai hajautetusti ja integroida tämä valinta sopivien kuljetusmuotojen kanssa. Aasiasta Pohjois-Eurooppaan on halpaa käyttää merikuljetusta, mutta operaatio kestää hyvin pitkään - joissain tapauksessa jopa kahdeksan viikkoa. Toisaalta lentokuljetus on sekä kallis että rajoittaa siirrettävien tuotteiden eräkokoa.On olemassa kolmaskin vaihtoehto, josta voisi olla ratkaisuksi: rautatiekuljetus on halvempi kuin lentokuljetus ja vasteajat ovat lyhyemmät kuin merikuljetuksissa. Tässä tutkimuksessa tilannetta selvitetään kyselyllä, joka suunnattiin Suomessa ja Ruotsissa toimiville yrityksille. Tuloksien perusteella teemme johtopäätökset siitä, mitkä kuljetusmuotojen markkinaosuudet tulevat olemaan tulevaisuudessa sekä luomme kuvan kuljetusvirroista Euroopan, Venäjän, Etelä-Korea, Intian, Kiinan ja Japanin välillä. Samalla on tarkoitus ennakoida sitä, miten tarkastelun kohteena olevat yritykset aikovat kehittää kuljetuksiaan ja varastointiaan tulevien vuosien aikana. Tulosten perusteella näyttää siltä, että seuraavan viiden vuoden kuluessa kuljetuskustannukset eivät merkittävissä määrin tule muuttuman ja meri- sekä kumipyöräkuljetukset pysyvät suosituimpina vaihtoehtoina.Kuitenkin lentokuljetusten osuus laskee hiukan, kun taas rautatiekuljetusten painotus kasvaa. Tulokset paljastavat, että Kiinassa ja Venäjällä kuljetettava konttimäärä kasvaa; Intiassa tulos on saman suuntainen, joskaan ei niin voimakas. Analyysimme mukaan kuljetusvirtoihin liittyvä epätasapaino säilyy Venäjän kuljetusten suhteen: yritykset jatkavat tulevaisuudessakin vientiperusteista strategiaansa. Varastoinnin puolella tunnistamme pienemmän muutoksen, jonka mukaan pienikokoisten varastojen määrät todennäköisesti vähenevät tulevaisuudessa ja kiinnostus isoja varastoja kohtaan lisääntyy. Tässä kohtaa on mainittava, että suomalaisilla yrityksillä on enemmän varastoja Keski- ja Itä-Euroopassa verrattuna ruotsalaisiin toimijoihin, jotka keskittyvät selkeämmin Länsi-Euroopan maihin. Varastoja yrityksillä on molemmissa tapaukissa paljolti kotimaassaan. Valitessaan varastojensa sijoituskohteita yritykset painottavat seuraavia kriteereitä: alhaiset jakelukustannukset, kokoamispaikan/valmistustehtaan läheisyys, saapuvan logistiikan integroitavuus ja saatavilla olevat logistiikkapalvelut. Tutkimuksemme lopussa päädymme siihen, että varastojen sijoituspaikat eivät muutu satamien rakenteen ja liikenneyhteyksien takia kovinkaan nopeasti.

Optimization of short term power trading between Russia, Finland and Baltic countries

Russian and Baltic electricity markets are in the process of reformation and development on the way for competitive and transparent market. Nordic market also undergoes some changes on the way to market integration. Old structure and practices have been expired whereas new laws and rules come into force. The master thesis describes structure and functioning of wholesale electricity markets, cross-border connections between different countries. Additionally methods of cross-border trading using different methods of capacity allocation are disclosed. The main goal of present thesis is to study current situation at different electricity markets and observe changes coming into force as well as the capacity and electricity balances forecast in order to optimize short term power trading between countries and estimate the possible profit for the company.

Drivers and Barriers of Collaboration in the Value Chain of Paperboard-Packed Consumer Goods

Value chain collaboration has been a prevailing topic for research, and there is a constantly growing interest in developing collaborative models for improved efficiency in logistics. One area of collaboration is demand information management, which enables improved visibility and decrease of inventories in the value chain. Outsourcing of non-core competencies has changed the nature of collaboration from intra-enterprise to cross-enterprise activity, and this together with increasing competition in the globalizing markets have created a need for methods and tools for collaborative work. The retailer part in the value chain of consumer packaged goods (CPG) has been studied relatively widely, proven models have been defined, and there exist several best practice collaboration cases. The information and communications technology has developed rapidly, offering efficient solutions and applications to exchange information between value chain partners. However, the majority of CPG industry still works with traditional business models and practices. This concerns especially companies operating in the upstream of the CPG value chain. Demand information for consumer packaged goods originates at retailers' counters, based on consumers' buying decisions. As this information does not get transferred along the value chain towards the upstream parties, each player needs to optimize their part, causing safety margins for inventories and speculation in purchasing decisions. The safety margins increase with each player, resulting in a phenomenon known as the bullwhip effect. The further the company is from the original demand information source, the more distorted the information is. This thesis concentrates on the upstream parts of the value chain of consumer packaged goods, and more precisely the packaging value chain. Packaging is becoming a part of the product with informative and interactive features, and therefore is not just a cost item needed to protect the product. The upstream part of the CPG value chain is distinctive, as the product changes after each involved party, and therefore the original demand information from the retailers cannot be utilized as such – even if it were transferred seamlessly. The objective of this thesis is to examine the main drivers for collaboration, and barriers causing the moderate adaptation level of collaborative models. Another objective is to define a collaborative demand information management model and test it in a pilot business situation in order to see if the barriers can be eliminated. The empirical part of this thesis contains three parts, all related to the research objective, but involving different target groups, viewpoints and research approaches. The study shows evidence that the main barriers for collaboration are very similar to the barriers in the lower part of the same value chain; lack of trust, lack of business case and lack of senior management commitment. Eliminating one of them – the lack of business case – is not enough to eliminate the two other barriers, as the operational model in this thesis shows. The uncertainty of the future, fear of losing an independent position in purchasing decision making and lack of commitment remain strong enough barriers to prevent the implementation of the proposed collaborative business model. The study proposes a new way of defining the value chain processes: it divides the contracting and planning process into two processes, one managing the commercial parts and the other managing the quantity and specification related issues. This model can reduce the resistance to collaboration, as the commercial part of the contracting process would remain the same as in the traditional model. The quantity/specification-related issues would be managed by the parties with the best capabilities and resources, as well as access to the original demand information. The parties in between would be involved in the planning process as well, as their impact for the next party upstream is significant. The study also highlights the future challenges for companies operating in the CPG value chain. The markets are becoming global, with toughening competition. Also, the technology development will most likely continue with a speed exceeding the adaptation capabilities of the industry. Value chains are also becoming increasingly dynamic, which means shorter and more agile business relationships, and at the same time the predictability of consumer demand is getting more difficult due to shorter product life cycles and trends. These changes will certainly have an effect on companies' operational models, but it is very difficult to estimate when and how the proven methods will gain wide enough adaptation to become standards.

Essays on pricing of risk and international linkage of Russian stock market

Last two decades have seen a rapid change in the global economic and financial situation; the economic conditions in many small and large underdeveloped countries started to improve and they became recognized as emerging markets. This led to growth in the amounts of global investments in these countries, partly spurred by expectations of higher returns, favorable risk-return opportunities, and better diversification alternatives to global investors. This process, however, has not been without problems and it has emphasized the need for more information on these markets. In particular, the liberalization of financial markets around the world, globalization of trade and companies, recent formation of economic and regional blocks, and the rapid development of underdeveloped countries during the last two decades have brought a major challenge to the financial world and researchers alike. This doctoral dissertation studies one of the largest emerging markets, namely Russia. The motivation why the Russian equity market is worth investigating includes, among other factors, its sheer size, rapid and robust economic growth since the turn of the millennium, future prospect for international investors, and a number of important major financial reforms implemented since the early 1990s. Another interesting feature of the Russian economy, which gives motivation to study Russian market, is Russia’s 1998 financial crisis, considered as one of the worst crisis in recent times, affecting both developed and developing economies. Therefore, special attention has been paid to Russia’s 1998 financial crisis throughout this dissertation. This thesis covers the period from the birth of the modern Russian financial markets to the present day, Special attention is given to the international linkage and the 1998 financial crisis. This study first identifies the risks associated with Russian market and then deals with their pricing issues. Finally some insights about portfolio construction within Russian market are presented. The first research paper of this dissertation considers the linkage of the Russian equity market to the world equity market by examining the international transmission of the Russia’s 1998 financial crisis utilizing the GARCH-BEKK model proposed by Engle and Kroner. Empirical results shows evidence of direct linkage between the Russian equity market and the world market both in regards of returns and volatility. However, the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market, even though the contagion can be clearly seen during the time of the crisis period. The second and the third paper, co-authored with Mika Vaihekoski, investigate whether global, local and currency risks are priced in the Russian stock market from a US investors’ point of view. Furthermore, the dynamics of these sources of risk are studied, i.e., whether the prices of the global and local risk factors are constant or time-varying over time. We utilize the multivariate GARCH-M framework of De Santis and Gérard (1998). Similar to them we find price of global market risk to be time-varying. Currency risk also found to be priced and highly time varying in the Russian market. Moreover, our results suggest that the Russian market is partially segmented and local risk is also priced in the market. The model also implies that the biggest impact on the US market risk premium is coming from the world risk component whereas the Russian risk premium is on average caused mostly by the local and currency components. The purpose of the fourth paper is to look at the relationship between the stock and the bond market of Russia. The objective is to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The Constant Conditional Correlation model by Bollerslev (1990), the Dynamic Conditional Correlation model by Engle (2002), and an asymmetric version of the Dynamic Conditional Correlation model by Cappiello et al. (2006) are used in the analysis. The empirical results do not support the assumption of constant conditional correlation and there was clear evidence of time varying correlations between the Russian stocks and bond market and both asset markets exhibit positive asymmetries. The implications of the results in this dissertation are useful for both companies and international investors who are interested in investing in Russia. Our results give useful insights to those involved in minimising or managing financial risk exposures, such as, portfolio managers, international investors, risk analysts and financial researchers. When portfolio managers aim to optimize the risk-return relationship, the results indicate that at least in the case of Russia, one should account for the local market as well as currency risk when calculating the key inputs for the optimization. In addition, the pricing of exchange rate risk implies that exchange rate exposure is partly non-diversifiable and investors are compensated for bearing the risk. Likewise, international transmission of stock market volatility can profoundly influence corporate capital budgeting decisions, investors’ investment decisions, and other business cycle variables. Finally, the weak integration of the Russian market and low correlations between Russian stock and bond market offers good opportunities to the international investors to diversify their portfolios.

Modeling and Analysis of Noise and Interconnects for On-Chip Communication Link Design

This thesis considers modeling and analysis of noise and interconnects in onchip communication. Besides transistor count and speed, the capabilities of a modern design are often limited by on-chip communication links. These links typically consist of multiple interconnects that run parallel to each other for long distances between functional or memory blocks. Due to the scaling of technology, the interconnects have considerable electrical parasitics that affect their performance, power dissipation and signal integrity. Furthermore, because of electromagnetic coupling, the interconnects in the link need to be considered as an interacting group instead of as isolated signal paths. There is a need for accurate and computationally effective models in the early stages of the chip design process to assess or optimize issues affecting these interconnects. For this purpose, a set of analytical models is developed for on-chip data links in this thesis. First, a model is proposed for modeling crosstalk and intersymbol interference. The model takes into account the effects of inductance, initial states and bit sequences. Intersymbol interference is shown to affect crosstalk voltage and propagation delay depending on bus throughput and the amount of inductance. Next, a model is proposed for the switching current of a coupled bus. The model is combined with an existing model to evaluate power supply noise. The model is then applied to reduce both functional crosstalk and power supply noise caused by a bus as a trade-off with time. The proposed reduction method is shown to be effective in reducing long-range crosstalk noise. The effects of process variation on encoded signaling are then modeled. In encoded signaling, the input signals to a bus are encoded using additional signaling circuitry. The proposed model includes variation in both the signaling circuitry and in the wires to calculate the total delay variation of a bus. The model is applied to study level-encoded dual-rail and 1-of-4 signaling. In addition to regular voltage-mode and encoded voltage-mode signaling, current-mode signaling is a promising technique for global communication. A model for energy dissipation in RLC current-mode signaling is proposed in the thesis. The energy is derived separately for the driver, wire and receiver termination.

Simulation and optimization of IGCC technique for power generation and hydrogen production by using lignite Thar coal and cotton stalk

The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

Use of preclinical and early clinical data for dose selection of a selective estrogen receptor modulator toremifene in treatment of breast cancer

In development of human medicines, it is important to predict early and accurately enough the disease and patient population to be treated as well as the effective and safe dose range of the studied medicine. This is pursued by using preclinical research models, clinical pharmacology and early clinical studies with small sample sizes. When successful, this enables effective development of medicines and reduces unnecessary exposure of healthy subjects and patients to ineffectice or harmfull doses of experimental compounds. Toremifene is a selective estrogen receptor modulator (SERM) used for treatment of breast cancer. Its development was initiated in 1980s when selection of treatment indications and doses were based on research in cell and animal models and on noncomparative clinical studies including small number of patients. Since the early development phase, the treatment indication, the patient population and the dose range were confirmed in large comparative clinical studies in patients. Based on the currently available large and long term clinical study data the aim of this study was to investigate how the early phase studies were able to predict the treatment indication, patient population and the dose range of the SERM. As a conclusion and based on the estrogen receptor mediated mechanism of action early studies were able to predict the treatment indication, target patient population and a dose range to be studied in confirmatory clinical studies. However, comparative clinical studies are needed to optimize dose selection of the SERM in treatment of breast cancer.

Benefits and challenges of supply chain finance business process automation : A case study in ING Bank

Supply chain finance, a financial product provided by the bank, has gained increasing attention and popularity over the last few years. Supply chain finance helps the corporate clients to optimize their financial flows along the supply chain. One characteristic of supply chain finance is that it aims to provide automated solutions. Therefore, the business process automation of supply chain finance is a very interesting and important topic for study. In this study, the business process automation of supply chain finance within the case organization, ING, is analysed. The purpose is to: (1) Identify the benefits to understand the importance to automate supply chain finance business process; (2) Find out the existing automation degree in the supply chain finance business process within the case bank to see what’s the situation now and how to improve in the future; (3) Discover the challenges in the further automation of supply chain finance business process. Firstly, the study finds out that supply chain finance business process automation can bring many benefits to the bank. Automation can improve productivity by using less time and human labour in the business process, and by providing scalable solutions. Automation can also improve quality of the service by reducing the human errors. Last but not least, automation can improve internal governance by providing enhanced visibility of the business process. Because of these potential benefits, many banks are actively seeking solutions to automate their supply chain finance business process. Then, the current automation situation with the case bank is analysed with the help of business process modelling. The supply chain finance business process within the case bank can be further divided into several sub processes: daily transaction, buyer sales and setup, supplier onboarding, contract management, customer services and supports, and contract termination. The study finds out that the daily transaction process is already a highly automated, which is carried out through the web-based trading platform. However, for other business the automation degree is relatively low. Among these business processes, supplier onboarding is most needed for further automation. Then, some solutions are also suggested to automate the supplier onboarding business process. In the end, the study also foresees some challenges during the further automation of supply chain finance business process in the case bank. Some suggestions are also given to deal with these challenges.

Automatic system identification and optimization of centrifugal pump operation

Centrifugal pumps are a notable end-consumer of electrical energy. Typical application of a centrifugal pump is the filling or emptying of a reservoir tank, where the pump is often operated at a constant speed until the process is completed. Installing a frequency converter to control the motor substitutes the traditional fixed-speed pumping system, allows the optimization of rotational speed profile for the pumping tasks and enables the estimation of rotational speed and shaft torque of an induction motor without any additional measurements from the motor shaft. Utilization of variable-speed operation provides the possibility to decrease the overall energy consumption of the pumping task. The static head of the pumping process may change during the pumping task. In such systems, the minimum rotational speed changes during reservoir filling or emptying, and the minimum energy consumption can’t be achieved with a fixed rotational speed. This thesis presents embedded algorithms to automatically identify, optimize and monitor pumping processes between supply and destination reservoirs, and evaluates the changing static head –based optimization method.

Search and Paper SKU Analysis of Recipes Meeting EUPS Standard

The theoretical research of the study concentrated on finding theoretical frameworks to optimize the amount of needed stock keeping units (SKUs) in manufacturing industry. The goal was to find ways for a company to acquire an optimal collection of stock keeping units needed for manufacturing needed amount of end products. The research follows constructive research approach leaning towards practical problem solving. In the empirical part of this study, a recipe search tool was developed to an existing database used in the target company. The purpose of the tools was to find all the recipes meeting the EUPS performance standard and put the recipes in a ranking order using the data available in the database. The ranking of the recipes was formed from the combination of the performance measures and price of the recipes. In addition, the tool researched what kind of paper SKUs were needed to manufacture the best performing recipes. The tool developed during this process meets the requirements. It eases and makes it much faster to search for all the recipes meeting the EUPS standard. Furthermore, many future development possibilities for the tool were discovered while writing the thesis.

University Institutional Repository and its Place in the University Information Infrastructure

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

NIR-Vis Up-Conversion Luminescence in the Yb3+,Er3+ Doped Y2O2S, ZrO2, and NaYF4 Nanomaterials

Since the discovery of the up-conversion phenomenon, there has been an ever increasing interest in up-converting phosphors in which the absorption of two or more low energy photons is followed by emission of a higher energy photon. Most up-conversion luminescence materials operate by using a combination of a trivalent rare earth (lanthanide) sensitizer (e.g. Yb or Er) and an activator (e.g. Er, Ho, Tm or Pr) ion in a crystal lattice. Up-converting phosphors have a variety of potential applications as lasers and displays as well as inks for security printing (e.g. bank notes and bonds). One of the most sophisticated applications of lanthanide up-conversion luminescence is probably in medical diagnostics. However, there are some major problems in the use of photoluminescence based on the direct UV excitation in immunoassays. Human blood absorbs strongly UV radiation as well as the emission of the phosphor in the visible. A promising way to overcome the problems arising from the blood absorption is to use a long wavelength excitation and benefit from the up-conversion luminescence. Since there is practically no absorption by the whole-blood in the near IR region, it has no capability for up-conversion in the excitation wavelength region of the conventional up-converting phosphor based on the Yb3+ (sensitizer) and Er3+ (activator) combination. The aim of this work was to prepare nanocrystalline materials with high red (and green) up-conversion luminescence efficiency for use in quantitative whole-blood immunoassays. For coupling to biological compounds, nanometer-sized (crystallite size below 50 nm) up-converting phosphor particles are required. The nanocrystalline ZrO2:Yb3+,Er3+, Y2O2S:Yb3+,Er3+, NaYF4:Yb3+,Er3+ and NaRF4-NaR’F4 (R: Y, Yb, Er) materials, prepared with the combustion, sol-gel, flux, co-precipitation and solvothermal synthesis, were studied using the thermal analysis, FT-IR spectroscopy, transmission electron microscopy, EDX spectroscopy, XANES/EXAFS measurements, absorption spectroscopy, X-ray powder diffraction, as well as up-conversion and thermoluminescence spectroscopies. The effect of the impurities of the phosphors, crystallite size, as well as the crystal structure on the up-conversion luminescence intensity was analyzed. Finally, a new phenomenon, persistent up-conversion luminescence was introduced and discussed. For efficient use in bioassays, more work is needed to yield nanomaterials with smaller and more uniform crystallite sizes. Surface modifications need to be studied to improve the dispersion in water. On the other hand, further work must be carried out to optimize the persistent up-conversion luminescence of the nanomaterials to allow for their use as efficient immunoassay nanomaterials combining the advantages of both up-conversion and persistent luminescence.

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.

Comparison of Different Concentrated Solar Power Collector Designs and Development of a Linear Fresnel Solar Collector Model

Concentrated solar power (CSP) is a renewable energy technology, which could contribute to overcoming global problems related to pollution emissions and increasing energy demand. CSP utilizes solar irradiation, which is a variable source of energy. In order to utilize CSP technology in energy production and reliably operate a solar field including thermal energy storage system, dynamic simulation tools are needed in order to study the dynamics of the solar field, to optimize production and develop control systems. The object of this Master’s Thesis is to compare different concentrated solar power technologies and configure a dynamic solar field model of one selected CSP field design in the dynamic simulation program Apros, owned by VTT and Fortum. The configured model is based on German Novatec Solar’s linear Fresnel reflector design. Solar collector components including dimensions and performance calculation were developed, as well as a simple solar field control system. The preliminary simulation results of two simulation cases under clear sky conditions were good; the desired and stable superheated steam conditions were maintained in both cases, while, as expected, the amount of steam produced was reduced in the case having lower irradiation conditions. As a result of the model development process, it can be concluded, that the configured model is working successfully and that Apros is a very capable and flexible tool for configuring new solar field models and control systems and simulating solar field dynamic behaviour.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.