Simulating and Forecasting the Demand for New Consumer Durables

A diffusion/replacement model for new consumer durables designed to be used as a long-term forecasting tool is developed. The model simulates new demand as well as replacement demand over time. The model is called DEMSIM and is built upon a counteractive adoption model specifying the basic forces affecting the adoption behaviour of individual consumers. These forces are the promoting forces and the resisting forces. The promoting forces are further divided into internal and external influences. These influences are operationalized within a multi-segmental diffusion model generating the adoption behaviour of the consumers in each segment as an expected value. This diffusion model is combined with a replacement model built upon the same segmental structure as the diffusion model. This model generates, in turn, the expected replacement behaviour in each segment. To be able to use DEMSIM as a forecasting tool in early stages of a diffusion process estimates of the model parameters are needed as soon as possible after product launch. However, traditional statistical techniques are not very helpful in estimating such parameters in early stages of a diffusion process. To enable early parameter calibration an optimization algorithm is developed by which the main parameters of the diffusion model can be estimated on the basis of very few sales observations. The optimization is carried out in iterative simulation runs. Empirical validations using the optimization algorithm reveal that the diffusion model performs well in early long-term sales forecasts, especially as it comes to the timing of future sales peaks.

Optimization of sample preparation for next-generation sequencing with Illumina Genome Analyzer II

The growing interest for sequencing with higher throughput in the last decade has led to the development of new sequencing applications. This thesis concentrates on optimizing DNA library preparation for Illumina Genome Analyzer II sequencer. The library preparation steps that were optimized include fragmentation, PCR purification and quantification. DNA fragmentation was performed with focused sonication in different concentrations and durations. Two column based PCR purification method, gel matrix method and magnetic bead based method were compared. Quantitative PCR and gel electrophoresis in a chip were compared for DNA quantification. The magnetic bead purification was found to be the most efficient and flexible purification method. The fragmentation protocol was changed to produce longer fragments to be compatible with longer sequencing reads. Quantitative PCR correlates better with the cluster number and should thus be considered to be the default quantification method for sequencing. As a result of this study more data have been acquired from sequencing with lower costs and troubleshooting has become easier as qualification steps have been added to the protocol. New sequencing instruments and applications will create a demand for further optimizations in future.

Inventory Routing - A Strategic Management Accounting Perspective

This dissertation develops a strategic management accounting perspective of inventory routing. The thesis studies the drivers of cost efficiency gains by identifying the role of the underlying cost structure, demand, information sharing, forecasting accuracy, service levels, vehicle fleet, planning horizon and other strategic factors as well as the interaction effects among these factors with respect to performance outcomes. The task is to enhance the knowledge of the strategic situations that favor the implementation of inventory routing systems, understanding cause-and-effect relationships, linkages and gaining a holistic view of the value proposition of inventory routing. The thesis applies an exploratory case study design, which is based on normative quantitative empirical research using optimization, simulation and factor analysis. Data and results are drawn from a real world application to cash supply chains. The first research paper shows that performance gains require a common cost component and cannot be explained by simple linear or affine cost structures. Inventory management and distribution decisions become separable in the absence of a set-dependent cost structure, and neither economies of scope nor coordination problems are present in this case. The second research paper analyzes whether information sharing improves the overall forecasting accuracy. Analysis suggests that the potential for information sharing is limited to coordination of replenishments and that central information do not yield more accurate forecasts based on joint forecasting. The third research paper develops a novel formulation of the stochastic inventory routing model that accounts for minimal service levels and forecasting accuracy. The developed model allows studying the interaction of minimal service levels and forecasting accuracy with the underlying cost structure in inventory routing. Interestingly, results show that the factors minimal service level and forecasting accuracy are not statistically significant, and subsequently not relevant for the strategic decision problem to introduce inventory routing, or in other words, to effectively internalize inventory management and distribution decisions at the supplier. Consequently the main contribution of this thesis is the result that cost benefits of inventory routing are derived from the joint decision model that accounts for the underlying set-dependent cost structure rather than the level of information sharing. This result suggests that the value of information sharing of demand and inventory data is likely to be overstated in prior literature. In other words, cost benefits of inventory routing are primarily determined by the cost structure (i.e. level of fixed costs and transportation costs) rather than the level of information sharing, joint forecasting, forecasting accuracy or service levels.

Wood procurement in the pressure of change.

Linear optimization model was used to calculate seven wood procurement scenarios for years 1990, 2000 and 2010. Productivity and cost functions for seven cutting, five terrain transport, three long distance transport and various work supervision and scaling methods were calculated from available work study reports. All method's base on Nordic cut to length system. Finland was divided in three parts for description of harvesting conditions. Twenty imaginary wood processing points and their wood procurement areas were created for these areas. The procurement systems, which consist of the harvesting conditions and work productivity functions, were described as a simulation model. In the LP-model the wood procurement system has to fulfil the volume and wood assortment requirements of processing points by minimizing the procurement cost. The model consists of 862 variables and 560 restrictions. Results show that it is economical to increase the mechanical work in harvesting. Cost increment alternatives effect only little on profitability of manual work. The areas of later thinnings and seed tree- and shelter wood cuttings increase on cost of first thinnings. In mechanized work one method, 10-tonne one grip harvester and forwarder, is gaining advantage among other methods. Working hours of forwarder are decreasing opposite to the harvester. There is only little need to increase the number of harvesters and trucks or their drivers from today's level. Quite large fluctuations in level of procurement and cost can be handled by constant number of machines, by alternating the number of season workers and by driving machines in two shifts. It is possible, if some environmental problems of large scale summer time harvesting can be solved.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Towards Understanding Powder Behavior Via Simulation

The aim of this study was to investigate powder and tablet behavior at the level of mechanical interactions between single particles. Various aspects of powder packing, mixing, compression, and bond formation were examined with the aid of computer simulations. The packing and mixing simulations were based on spring forces interacting between particles. Packing and breakage simulations included systems in which permanent bonds were formed and broken between particles, based on their interaction strengths. During the process, a new simulation environment based on Newtonian mechanics and elementary interactions between the particles was created, and a new method for evaluating mixing was developed. Powder behavior is a complicated process, and many of its aspects are still unclear. Powders as a whole exhibit some aspects of solids and others of liquids. Therefore, their physics is far from clear. However, using relatively simple models based on particle-particle interaction, many powder properties could be replicated during this work. Simulated packing densities were similar to values reported in the literature. The method developed for describing powder mixing correlated well with previous methods. The new method can be applied to determine mixing in completely homogeneous materials, without dividing them into different components. As such, it can describe the efficiency of the mixing method, regardless of the powder's initial setup. The mixing efficiency at different vibrations was examined, and we found that certain combinations of amplitude, direction, and frequencies resulted in better mixing while using less energy. Simulations using exponential force potentials between particles were able to explain the elementary compression behavior of tablets, and create force distributions that were similar to the pressure distributions reported in the literature. Tablet-breaking simulations resulted in breaking strengths that were similar to measured tablet breaking strengths. In general, many aspects of powder behavior can be explained with mechanical interactions at the particle level, and single particle properties can be reliably linked to powder behavior with accurate simulations.

Optimizing simulation model on forest policy.

XVIII IUFRO World Congress, Ljubljana 1986.

Forest sector simulation models as methodological tools in forest policy analysis.

XVIII IUFRO World Congress, Ljubljana 1986.

Application of an ecological simulation model to Lake Päijänne

Tiivistelmä: Simulointimallin soveltaminen Pohjois-Päijänteellä

Computer simulation of multi-elemental fusion reactor materials

Thermonuclear fusion is a sustainable energy solution, in which energy is produced using similar processes as in the sun. In this technology hydrogen isotopes are fused to gain energy and consequently to produce electricity. In a fusion reactor hydrogen isotopes are confined by magnetic fields as ionized gas, the plasma. Since the core plasma is millions of degrees hot, there are special needs for the plasma-facing materials. Moreover, in the plasma the fusion of hydrogen isotopes leads to the production of high energetic neutrons which sets demanding abilities for the structural materials of the reactor. This thesis investigates the irradiation response of materials to be used in future fusion reactors. Interactions of the plasma with the reactor wall leads to the removal of surface atoms, migration of them, and formation of co-deposited layers such as tungsten carbide. Sputtering of tungsten carbide and deuterium trapping in tungsten carbide was investigated in this thesis. As the second topic the primary interaction of the neutrons in the structural material steel was examined. As model materials for steel iron chromium and iron nickel were used. This study was performed theoretically by the means of computer simulations on the atomic level. In contrast to previous studies in the field, in which simulations were limited to pure elements, in this work more complex materials were used, i.e. they were multi-elemental including two or more atom species. The results of this thesis are in the microscale. One of the results is a catalogue of atom species, which were removed from tungsten carbide by the plasma. Another result is e.g. the atomic distributions of defects in iron chromium caused by the energetic neutrons. These microscopic results are used in data bases for multiscale modelling of fusion reactor materials, which has the aim to explain the macroscopic degradation in the materials. This thesis is therefore a relevant contribution to investigate the connection of microscopic and macroscopic radiation effects, which is one objective in fusion reactor materials research.