Toll issues

Bakalářská práce se zabývá problematikou výběru mýta na silniční síti. První část práce popisuje zavedené způsoby zpoplatnění komunikací a klade důraz na zpoplatnění výkonové. Zabývá se elektronickými mýtnými systémy a mikrovlnnou technologií, používanou v České republice. V druhé části je uveden výběr poplatků za užívání pozemních komunikací, činnost Celní správy a telematické systémy. Třetí část je zaměřena na rozšíření zpoplatnění silnic I. a II. třídy, na náklady na zavedení a provozování výběru mýta. Čtvrtá část popisuje problematiku a zhodnocení systému zavedení, rozšiřování a výběru mýta.The bachelor thesis deals with the issues of toll collection in the road network. The first part of the work describes the established tolling methods and focuses on volume-distance tolling. It deals with electronic toll collection systems and the microwave toll technology used in the Czech Republic. The second part focuses on the fees charged for use of road network, function of the Customs Administration and telematic systems. The third part centers on the extension of toll to second- and third-class roads and the costs of implementation and managment of toll collection. The fourth part of the work discusses the issues and evaluation of the system of implementation, extension and collection of toll.

Exploiting structure in integer programs

The thesis argues the case for exploiting certain structures in integer linear programs. Integer linear programs are optimisation problems, where one minimises or maximises a linear function of variables, whose values are required to be integral as well as satisfying certain linear equalities and inequalities. For such an abstract problem, there are very good general-purpose solvers. The state of the art in such solvers is an approach known as “branch and bound”. The performance of such solvers depends crucially on four types of in-built heuristics: primal, improvement, branching, and cut-separation or, more generally, bounding heuristics. However, such heuristics have, until recently, not exploited structure in integer linear programs beyond the recognition of certain types of single-row constraints. Many alternative approaches to integer linear programming can be cast in the following, novel framework. “Structure” in any integer linear program is a class of equivalence among triples of algorithms: deriving combinatorial objects from the input, adapting them, and transforming the adapted object to solutions of the original integer linear program. Many such alternative approaches are, however, inherently incompatible with branch and bound solvers. We, hence, define a structure to be “useful”, only when it extracts submatrices, which allow for the implementation of more than one of the four types of heuristics required in the branch and bound approach. Although the extraction of the best possible submatrices is non-trivial, the lack of a considerable submatrix with a given property can often be recognised quickly, and storing useful submatrices in a “pool” makes it possible to use them repeatedly. The goal is to explore whether the state-of-the-art solvers could make use of the structures studied in the academia. Three examples of useful structures in integer linear programs are presented. A particularly widely applicable useful structure relies on the aggregation of variables. Its application can be seen as a decomposition into three stages: Firstly, we partition variables in the original instance into as small number as possible of support sets of constraints forcing convex combinations of binary variables to be less than or equal to one in the original instance, and one-element sets. Secondly, we solve the “aggregated” instance corresponding to the partition of variables. Under certain conditions, we obtain a valid lower bound. Finally, we fix the solution of the aggregated instance in primal and improvement heuristics for the original instance, and use the partition in hyper-plane branching heuristics. Under certain conditions, the primal heuristics are guaranteed to find a feasible solution to the original instance. We also present structures exploiting mutual-exclusion and precedence constraints, prevalent in scheduling and timetabling applications. Mutual exclusion constraints correspond to instances of graph colouring. For numerous extensions of graph colouring, there are natural primal and branching heuristics. We present lower bounding heuristics for extensions of graph colouring, based on augmented Lagrangian methods for novel semidefinite programming relaxations, and reformulations based on a novel transformation of graph colouring to graph multicolouring. Precedence constraints correspond to an instance of precedence-constrained multi-dimensional packing. For such packing problems, we present heuristics based on an adaptive discretisation and strong discretised linear programming relaxations. On in- stances of packing unit-cubes into a box, the reformulation makes it possible to solve instances that are by five orders of magnitude larger than previously. On instances from complex timetabling problems, which combine mutual- exclusion and packing constraints, the combination of heuristics above can often result in the gap between primal and dual bounds being reduced to under five percent, orders of magnitude faster than using state of the art solvers, without any information being used that is outside of the instance

Decomposition, Reformulation, and Diving in University Course Timetabling

In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition, also known as the Udine Course Timetabling Problem. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.Comment: 45 pages, 7 figures. Improved typesetting of figures and table

Matrix Completion under Interval Uncertainty

Matrix completion under interval uncertainty can be cast as matrix completion with element-wise box constraints. We present an efficient alternating-direction parallel coordinate-descent method for the problem. We show that the method outperforms any other known method on a benchmark in image in-painting in terms of signal-to-noise ratio, and that it provides high-quality solutions for an instance of collaborative filtering with 100,198,805 recommendations within 5 minutes

Khresmoi Professional: Multilingual Semantic Search for Medical Professionals

There is increasing interest in and need for innovative solutions to medical search. In this paper we present the EU funded Khresmoi medical search and access system, currently in year 3 of 4 of development across 12 partners . The Khresmoi system uses a component based architecture housed in the cloud to allow for the development of several innovative applications to support target users medical information needs. The Khresmoi search systems based on this architecture have been designed to support the multilingual and multimod al information needs of three target groups the general public, general practitioners and consultant radiologists. In this paper we focus on the presentation of the systems to support the latter two groups using semantic, multilingual text and image based (including 2D and 3D radiology images) search

Copying you copying me:Interpersonal motor co-ordination influences automatic imitation

Moving in a co-ordinated fashion with another individual changes our behaviour towards them; we tend to like them more, find them more attractive, and are more willing to co-operate with them. It is generally assumed that this effect on behaviour results from alterations in representations of self and others. Specifically, through neurophysiological perception-action matching mechanisms, interpersonal motor co-ordination (IMC) is believed to forge a neural coupling between actor and observer, which serves to blur boundaries in conceptual self-other representations and causes positive views of the self to be projected onto others. An investigation into this potential neural mechanism is lacking, however. Moreover, the specific components of IMC that might influence this mechanism have not yet been specified. In the present study we exploited a robust behavioural phenomenon - automatic imitation - to assess the degree to which IMC influences neural action observation-execution matching mechanisms. This revealed that automatic imitation is reduced when the actions of another individual are perceived to be synchronised in time, but are spatially incongruent, with our own. We interpret our findings as evidence that IMC does indeed exert an effect on neural perception-action matching mechanisms, but this serves to promote better self-other distinction. Our findings demonstrate that further investigation is required to understand the complex relationship between neural perception-action coupling, conceptual self-other representations, and social behaviour

On a Clique-Based Integer Programming Formulation of Vertex Colouring with Applications in Course Timetabling

Vertex colouring is a well-known problem in combinatorial optimisation, whose alternative integer programming formulations have recently attracted considerable attention. This paper briefly surveys seven known formulations of vertex colouring and introduces a formulation of vertex colouring using a suitable clique partition of the graph. This formulation is applicable in timetabling applications, where such a clique partition of the conflict graph is given implicitly. In contrast with some alternatives, the presented formulation can also be easily extended to accommodate complex performance indicators (``soft constraints'') imposed in a number of real-life course timetabling applications. Its performance depends on the quality of the clique partition, but encouraging empirical results for the Udine Course Timetabling problem are reported

Population in the town of Telč in 18th century, based on sources of town and cadastral provenance

This diploma thesis deals with population in the town of Telč in 18th century, based on sources of town and cadastral provenance. The issue is of particular interest as it has not been researched in greater detail yet. At first, the thesis provides an introduction to the extant literature covering the history of Telč, assessing the authors' approach, what historical epoch they consider most prosperous and their perspective of the town in 18th century. Chapter II addresses sources of town and cadastral provenance, thus introducing and evaluating the sources the thesis is based on. Chapter III addresses the regulated municipal authority in Telč. Chapter IV provides an insight into the development of town population in the Bohemian lands in 17th and 18th centuries, which enables contextualizing Telč within the development. Chapter V is dedicated to the town itself, focusing on its history in the relevant period, the town's inhabitants, external description, the Inner Town and eventually, the social pattern of the inhabitants. The social pattern is described in a detailed analysis of three houses located on the town square and their owners. In the end I will describe property structure of the town councillors who were serving in office in 1762, 1766, 1768 and 1770

Exploiting structure in integer programs

The thesis argues the case for exploiting certain structures in integer linear programs. Integer linear programs are optimisation problems, where one minimises or maximises a linear function of variables, whose values are required to be integral as well as satisfying certain linear equalities and inequalities. For such an abstract problem, there are very good general-purpose solvers. The state of the art in such solvers is an approach known as “branch and bound”. The performance of such solvers depends crucially on four types of in-built heuristics: primal, improvement, branching, and cut-separation or, more generally, bounding heuristics. However, such heuristics have, until recently, not exploited structure in integer linear programs beyond the recognition of certain types of single-row constraints. Many alternative approaches to integer linear programming can be cast in the following, novel framework. “Structure” in any integer linear program is a class of equivalence among triples of algorithms: deriving combinatorial objects from the input, adapting them, and transforming the adapted object to solutions of the original integer linear program. Many such alternative approaches are, however, inherently incompatible with branch and bound solvers. We, hence, define a structure to be “useful”, only when it extracts submatrices, which allow for the implementation of more than one of the four types of heuristics required in the branch and bound approach. Although the extraction of the best possible submatrices is non-trivial, the lack of a considerable submatrix with a given property can often be recognised quickly, and storing useful submatrices in a “pool” makes it possible to use them repeatedly. The goal is to explore whether the state-of-the-art solvers could make use of the structures studied in the academia. Three examples of useful structures in integer linear programs are presented. A particularly widely applicable useful structure relies on the aggregation of variables. Its application can be seen as a decomposition into three stages: Firstly, we partition variables in the original instance into as small number as possible of support sets of constraints forcing convex combinations of binary variables to be less than or equal to one in the original instance, and one-element sets. Secondly, we solve the “aggregated” instance corresponding to the partition of variables. Under certain conditions, we obtain a valid lower bound. Finally, we fix the solution of the aggregated instance in primal and improvement heuristics for the original instance, and use the partition in hyper-plane branching heuristics. Under certain conditions, the primal heuristics are guaranteed to find a feasible solution to the original instance. We also present structures exploiting mutual-exclusion and precedence constraints, prevalent in scheduling and timetabling applications. Mutual exclusion constraints correspond to instances of graph colouring. For numerous extensions of graph colouring, there are natural primal and branching heuristics. We present lower bounding heuristics for extensions of graph colouring, based on augmented Lagrangian methods for novel semidefinite programming relaxations, and reformulations based on a novel transformation of graph colouring to graph multicolouring. Precedence constraints correspond to an instance of precedence-constrained multi-dimensional packing. For such packing problems, we present heuristics based on an adaptive discretisation and strong discretised linear programming relaxations. On in- stances of packing unit-cubes into a box, the reformulation makes it possible to solve instances that are by five orders of magnitude larger than previously. On instances from complex timetabling problems, which combine mutual- exclusion and packing constraints, the combination of heuristics above can often result in the gap between primal and dual bounds being reduced to under five percent, orders of magnitude faster than using state of the art solvers, without any information being used that is outside of the instance

Telč in seventeenth century

The topic of my bachelor's work is the history of the town of Telč in the 17th century. I chose this historical epoch mainly for the reason that little attention was devoted to it in previous research of Telč history. First, I evaluate the works that have been written about Telč so far. I try to assess the approach of their authors and I investigate which historical period of the town they considered to be the heyday of time. I also focus on their view of the town in the 17th century. Subsequently, I incorporate Telč to the urban network in early modern times. I compare its size not only to towns in the Telč County but also to the size of urban settlements in Bohemia and Moravia. Afterwards, I introduce the members of Slavata family individually and their relationship to the town. Then, I concentrate on the impact of the Thirty Years War on the town and the situation thereafter. Finally, I reconstruct the appearance of the town administration on the basis of extant sources, its functioning and relationship to the castle lords in the last chapter