Demographic Modelling of Human Population Growth

This work presents models and methods that have been used in producing forecasts of population growth. The work is intended to emphasize the reliability bounds of the model forecasts. Leslie model and various versions of logistic population models are presented. References to literature and several studies are given. A lot of relevant methodology has been developed in biological sciences. The Leslie modelling approach involves the use of current trends in mortality,fertility, migration and emigration. The model treats population divided in age groups and the model is given as a recursive system. Other group of models is based on straightforward extrapolation of census data. Trajectories of simple exponential growth function and logistic models are used to produce the forecast. The work presents the basics of Leslie type modelling and the logistic models, including multi- parameter logistic functions. The latter model is also analysed from model reliability point of view. Bayesian approach and MCMC method are used to create error bounds of the model predictions.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Feasibility of replacing multiple ADSL connections with Multi-Dwelling Access

This final project was made for the Broadband/Implementation department of TeliaSonera Finland. The question to be examined is if the operator should replace multiple ADSL connections implemented over a leased line with Multi-Dwelling access based on an Ethernet/Optical Fibre access network. The project starts with describing the technology related to these access network solu-tions and presents the technology that is used in TeliaSonera Finland's access network. It continues from the technology to describe the problem with some of the ADSL implemen-tations of TeliaSonera. The problem is the implementations done over a leased line that can cost TeliaSonera over years as much as a possible investment to extend network when there is several lines leased to the same building. The project proposes a Multi-Dwelling access as a solution to this problem and defines the circumstances when to use it. After a satisfactory solution has found the project takes a view how implementation of the solution might alter the network and a new problem is found. When used commonly to replace need of ADSL implementation Multi-Dwelling access would significantly increase optical cable congestion near operators POP. As a final deed this project also proposes a technical change to existing way to implement multi-dwelling access with EPON technology.

Optimizing the supply chain strategy of a multi-unit Finnish nursery company

Abstract

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.

Multi-site -sertifikaatin vaatimukset ympäristöjohtamisjärjestelmän rakentamisessa

Diplomityö muodostuu kahdesta kokonaisuudesta. Työn teoriaosa kertoo mitä ympäristöjohtaminen on, millaisia ovat multi-site -organisaatio ja multi-site -johtamisjärjestelmä sekä mitä vaatimuksia nämä asettavat yritykselle. Työssä esitetään malli, jota käyttämällä kansainvälisten johtamisjärjestelmästandardien mukaan rakennetut laatu-, ympäristö-, terveys- ja turvallisuusjärjestelmät voidaan yhdistää yhdeksi kokonaisuudeksi, multi-site - johtamisjärjestelmäksi. Malli rakentuu kolmesta tasosta, joita ovat paikallinen, maakohtainen ja konsernitaso. Esimerkkien avulla kerrotaan miteneri lähtökohdista voidaan näiden tasojen kautta edetä kohti yhtä johtamiskokonaisuutta. Esille tuodaan myös multi-site -johtamisjärjestelmän käyttöönottoa puoltavat ja vastustavat näkökohdat. Työn konkreettinen osa on johtamisjärjestelmämallin paikallisen tason toteuttaminen. Ympäristöjohtamisjärjestelmän rakentaminen standardin EN ISO 14001:2004 vaatimusten mukaiseksi Kvaerner Power Oy:n Suomen toimipaikoille sekä tämän järjestelmän yhdistäminen sertifioituun EN ISO 9001 -standardin mukaiseen laatujärjestelmään. Työssä kerrotaan miten ympäristöjohtamisjärjestelmä on rakennettu ja miten laatu- ja ympäristöjärjestelmät on liitetty yhdeksi kokonaisuudeksi. Työn tuloksena syntyi malli johtamisjärjestelmien yhdistämisestä sekä sertifioitu ympäristöjohtamisjärjestelmä, jonka yhdistäminen laatujärjestelmään toteutettiin tavoitteiden mukaisesti.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.