Branching Stochastic Processes: History, Theory, Applications

Косто В. Митов - Разклоняващите се стохастични процеси са модели на популационната динамика на обекти, които имат случайно време на живот и произвеждат потомци в съответствие с дадени вероятностни закони. Типични примери са ядрените реакции, клетъчната пролиферация, биологичното размножаване, някои химични реакции, икономически и финансови явления. В този обзор сме се опитали да представим съвсем накратко някои от най-важните моменти и факти от историята, теорията и приложенията на разклоняващите се процеси.

Controlled Multitype Branching Models: Geometric Growth

2000 Mathematics Subject Classi cation: 60J80, 60F25.

Branching Populations of Cells Bearing a Continuous Label

2000 Mathematics Subject Classification: 60J80.

Comparison between Numerical and Simulation Methods for Age-dependent Branching Models with Immigration

2000 Mathematics Subject Classification: primary: 60J80, 60J85, secondary: 62M09, 92D40

Some misspecfication problems in long-memory time series models

Doctor of Philosophy in Mathematics

A novel continuous time representation for the scheduling of pipeline systems with pumping yield rate constraints

Pipeline systems play a key role in the petroleum business. These operational systems provide connection between ports and/or oil fields and refineries (upstream), as well as between these and consumer markets (downstream). The purpose of this work is to propose a novel MINLP formulation based on a continuous time representation for the scheduling of multiproduct pipeline systems that must supply multiple consumer markets. Moreover, it also considers that the pipeline operates intermittently and that the pumping costs depend on the booster stations yield rates, which in turn may generate different flow rates. The proposed continuous time representation is compared with a previously developed discrete time representation [Rejowski, R., Jr., & Pinto, J. M. (2004). Efficient MILP formulations and valid cuts for multiproduct pipeline scheduling. Computers and Chemical Engineering, 28, 1511] in terms of solution quality and computational performance. The influence of the number of time intervals that represents the transfer operation is studied and several configurations for the booster stations are tested. Finally, the proposed formulation is applied to a larger case, in which several booster configurations with different numbers of stages are tested. (C) 2007 Elsevier Ltd. All rights reserved.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Swapping space for time and unfair tests of ecological models

Testing ecological models for management is an increasingly important part of the maturation of ecology as an applied science. Consequently, we need to work at applying fair tests of models with adequate data. We demonstrate that a recent test of a discrete time, stochastic model was biased towards falsifying the predictions. If the model was a perfect description of reality, the test falsified the predictions 84% of the time. We introduce an alternative testing procedure for stochastic models, and show that it falsifies the predictions only 5% of the time when the model is a perfect description of reality. The example is used as a point of departure to discuss some of the philosophical aspects of model testing.

Controling delayed transitions with applications to prevent single species extinctions

A new method is proposed to control delayed transitions towards extinction in single population theoretical models with discrete time undergoing saddle-node bifurcations. The control method takes advantage of the delaying properties of the saddle remnant arising after the bifurcation, and allows to sustain populations indefinitely. Our method, which is shown to work for deterministic and stochastic systems, could generally be applied to avoid transitions tied to one-dimensional maps after saddle-node bifurcations.

Insurance with frequent trading

This paper looks at the dynamic management of risk in an economy with discrete time consumption and endowments and continuous trading. I study how agents in such an economy deal with all the risk in the economy and attain their Pareto optimal allocations by trading in a few natural securities: private insurance contracts and a common set of derivatives on the aggregate endowment. The parsimonious nature ofthe implied securities needed for Pareto optimality suggests that insuch contexts complete markets is a very reasonable assumption.

Mechanistic population Models in Biology: Model Derivation and Application

In general, models of ecological systems can be broadly categorized as ’top-down’ or ’bottom-up’ models, based on the hierarchical level that the model processes are formulated on. The structure of a top-down, also known as phenomenological, population model can be interpreted in terms of population characteristics, but it typically lacks an interpretation on a more basic level. In contrast, bottom-up, also known as mechanistic, population models are derived from assumptions and processes on a more basic level, which allows interpretation of the model parameters in terms of individual behavior. Both approaches, phenomenological and mechanistic modelling, can have their advantages and disadvantages in different situations. However, mechanistically derived models might be better at capturing the properties of the system at hand, and thus give more accurate predictions. In particular, when models are used for evolutionary studies, mechanistic models are more appropriate, since natural selection takes place on the individual level, and in mechanistic models the direct connection between model parameters and individual properties has already been established. The purpose of this thesis is twofold. Firstly, a systematical way to derive mechanistic discrete-time population models is presented. The derivation is based on combining explicitly modelled, continuous processes on the individual level within a reproductive period with a discrete-time maturation process between reproductive periods. Secondly, as an example of how evolutionary studies can be carried out in mechanistic models, the evolution of the timing of reproduction is investigated. Thus, these two lines of research, derivation of mechanistic population models and evolutionary studies, are complementary to each other.

Problèmes de premier passage et de commande optimale pour des chaînes de Markov à temps discret.

Nous considérons des processus de diffusion, définis par des équations différentielles stochastiques, et puis nous nous intéressons à des problèmes de premier passage pour les chaînes de Markov en temps discret correspon- dant à ces processus de diffusion. Comme il est connu dans la littérature, ces chaînes convergent en loi vers la solution des équations différentielles stochas- tiques considérées. Notre contribution consiste à trouver des formules expli- cites pour la probabilité de premier passage et la durée de la partie pour ces chaînes de Markov à temps discret. Nous montrons aussi que les résultats ob- tenus convergent selon la métrique euclidienne (i.e topologie euclidienne) vers les quantités correspondantes pour les processus de diffusion. En dernier lieu, nous étudions un problème de commande optimale pour des chaînes de Markov en temps discret. L’objectif est de trouver la valeur qui mi- nimise l’espérance mathématique d’une certaine fonction de coût. Contraire- ment au cas continu, il n’existe pas de formule explicite pour cette valeur op- timale dans le cas discret. Ainsi, nous avons étudié dans cette thèse quelques cas particuliers pour lesquels nous avons trouvé cette valeur optimale.

Räumliche Modellierung der Dynamik von Landnutzung in Hessen und ihrer Wirkung auf die biologische Kohlenstoffspeicherung - Entwicklung eines GIS-basierten Modellsystems

Die gegenwärtige Entwicklung der internationalen Klimapolitik verlangt von Deutschland eine Reduktion seiner Treibhausgasemissionen. Wichtigstes Treibhausgas ist Kohlendioxid, das durch die Verbrennung fossiler Energieträger in die Atmosphäre freigesetzt wird. Die Reduktionsziele können prinzipiell durch eine Verminderung der Emissionen sowie durch die Schaffung von Kohlenstoffsenken erreicht werden. Senken beschreiben dabei die biologische Speicherung von Kohlenstoff in Böden und Wäldern. Eine wichtige Einflussgröße auf diese Prozesse stellt die räumliche Dynamik der Landnutzung einer Region dar. In dieser Arbeit wird das Modellsystem HILLS entwickelt und zur Simulation dieser komplexen Wirkbeziehungen im Bundesland Hessen genutzt. Ziel ist es, mit HILLS über eine Analyse des aktuellen Zustands hinaus auch Szenarien über Wege der zukünftigen regionalen Entwicklung von Landnutzung und ihrer Wirkung auf den Kohlenstoffhaushalt bis 2020 zu untersuchen. Für die Abbildung der räumlichen und zeitlichen Dynamik von Landnutzung in Hessen wird das Modell LUCHesse entwickelt. Seine Aufgabe ist die Simulation der relevanten Prozesse auf einem 1 km2 Raster, wobei die Raten der Änderung exogen als Flächentrends auf Ebene der hessischen Landkreise vorgegeben werden. LUCHesse besteht aus Teilmodellen für die Prozesse: (A) Ausbreitung von Siedlungs- und Gewerbefläche, (B) Strukturwandel im Agrarsektor sowie (C) Neuanlage von Waldflächen (Aufforstung). Jedes Teilmodell umfasst Methoden zur Bewertung der Standorteignung der Rasterzellen für unterschiedliche Landnutzungsklassen und zur Zuordnung der Trendvorgaben zu solchen Rasterzellen, die jeweils am besten für eine Landnutzungsklasse geeignet sind. Eine Validierung der Teilmodelle erfolgt anhand von statistischen Daten für den Zeitraum von 1990 bis 2000. Als Ergebnis eines Simulationslaufs werden für diskrete Zeitschritte digitale Karten der Landnutzugsverteilung in Hessen erzeugt. Zur Simulation der Kohlenstoffspeicherung wird eine modifizierte Version des Ökosystemmodells Century entwickelt (GIS-Century). Sie erlaubt einen gesteuerten Simulationslauf in Jahresschritten und unterstützt die Integration des Modells als Komponente in das HILLS Modellsystem. Es werden verschiedene Anwendungsschemata für GIS-Century entwickelt, mit denen die Wirkung der Stilllegung von Ackerflächen, der Aufforstung sowie der Bewirtschaftung bereits bestehender Wälder auf die Kohlenstoffspeicherung untersucht werden kann. Eine Validierung des Modells und der Anwendungsschemata erfolgt anhand von Feld- und Literaturdaten. HILLS implementiert eine sequentielle Kopplung von LUCHesse mit GIS-Century. Die räumliche Kopplung geschieht dabei auf dem 1 km2 Raster, die zeitliche Kopplung über die Einführung eines Landnutzungsvektors, der die Beschreibung der Landnutzungsänderung einer Rasterzelle während des Simulationszeitraums enthält. Außerdem integriert HILLS beide Modelle über ein dienste- und datenbankorientiertes Konzept in ein Geografisches Informationssystem (GIS). Auf diesem Wege können die GIS-Funktionen zur räumlichen Datenhaltung und Datenverarbeitung genutzt werden. Als Anwendung des Modellsystems wird ein Referenzszenario für Hessen mit dem Zeithorizont 2020 berechnet. Das Szenario setzt im Agrarsektor eine Umsetzung der AGENDA 2000 Politik voraus, die in großem Maße zu Stilllegung von Ackerflächen führt, während für den Bereich Siedlung und Gewerbe sowie Aufforstung die aktuellen Trends der Flächenausdehnung fortgeschrieben werden. Mit HILLS ist es nun möglich, die Wirkung dieser Landnutzungsänderungen auf die biologische Kohlenstoffspeicherung zu quantifizieren. Während die Ausdehnung von Siedlungsflächen als Kohlenstoffquelle identifiziert werden kann (37 kt C/a), findet sich die wichtigste Senke in der Bewirtschaftung bestehender Waldflächen (794 kt C/a). Weiterhin führen die Stilllegung von Ackerfläche (26 kt C/a) sowie Aufforstung (29 kt C/a) zu einer zusätzlichen Speicherung von Kohlenstoff. Für die Kohlenstoffspeicherung in Böden zeigen die Simulationsexperimente sehr klar, dass diese Senke nur von beschränkter Dauer ist.

An Extension to the Tactical Planning Model for a Job Shop: Continuous-Time Control

We develop an extension to the tactical planning model (TPM) for a job shop by the third author. The TPM is a discrete-time model in which all transitions occur at the start of each time period. The time period must be defined appropriately in order for the model to be meaningful. Each period must be short enough so that a job is unlikely to travel through more than one station in one period. At the same time, the time period needs to be long enough to justify the assumptions of continuous workflow and Markovian job movements. We build an extension to the TPM that overcomes this restriction of period sizing by permitting production control over shorter time intervals. We achieve this by deriving a continuous-time linear control rule for a single station. We then determine the first two moments of the production level and queue length for the workstation.

Application of a novel optimal control algorithm to a benchmark fed-batch fermentation process

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.