MATHEMATICAL SIMULATION FOR ASSESSMENT OF THE SMALL BUSINESS EFFICIENCY: REGIONAL ASPECTS

Mathematical simulation of economic systems and processes are considered. The description of macroeconomic models for assets formation, consumer behaviour, production activity of an enterprise, and market balance is given. The line balance model of diversified economic system is examined

Road User Charging – Pricing Structures.

This project considers the extent to which the public could cope with complex price or tariff structures such as those that might be considered in the context of a national congestion pricing scheme. The key elements of the brief were: • to review existing studies of road pricing schemes to assess what information and evidence already exists on the key issues; • to identify what can be learned about pricing structures from other transport modes and other industries and in particular what issues and conclusions might be transferable; • to improve the general understanding of the relationship between information and people’s ability to respond; and • to recommend what further research would be most valuable to fill evidence gaps and enable conclusions to be drawn about an effective structure

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning

We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available.Comment: arXiv admin note: text overlap with arXiv:1101.5184 by other author

Model-based Transportation Performance: A Comparative Framework and Literature Synthesis, Research Report 11-09

In an era of limited resources and a proliferation of data, there is increasing pressure to conduct careful evaluations of the economic, environmental, and equity effects of investments and policies that influence transportation and land-use systems. This report compares performance measures recommended to achieve desired goals and reviews the literature to determine the degree to which these measures have been implemented and what they indicate about the relative effectiveness of land-use, transit, and automobile pricing policies. Despite the variation in methods and performance measures implemented in the studies reviewed for this report, the synthesis of study results suggests the direction and relative magnitude of change resulting from different types of policies, as well as potential biases introduced by omitting the representation of the land-use and transportation interaction. Overall, the performance measures indicate that carefully designed transit, land-use, and automobile pricing policies may improve travel, economic, environmental, and equity conditions for communities. However, transit and peak-period automobile pricing policies can, in some situations, lead to negative performance outcomes across some or all measures, as illustrated in studies that explicitly represent the land-use and transportation interaction

A framework for managing global risk factors affecting construction cost performance

Poor cost performance of construction projects has been a major concern for both contractors and clients. The effective management of risk is thus critical to the success of any construction project and the importance of risk management has grown as projects have become more complex and competition has increased. Contractors have traditionally used financial mark-ups to cover the risk associated with construction projects but as competition increases and margins have become tighter they can no longer rely on this strategy and must improve their ability to manage risk. Furthermore, the construction industry has witnessed significant changes particularly in procurement methods with clients allocating greater risks to contractors. Evidence shows that there is a gap between existing risk management techniques and tools, mainly built on normative statistical decision theory, and their practical application by construction contractors. The main reason behind the lack of use is that risk decision making within construction organisations is heavily based upon experience, intuition and judgement and not on mathematical models. This thesis presents a model for managing global risk factors affecting construction cost performance of construction projects. The model has been developed using behavioural decision approach, fuzzy logic technology, and Artificial Intelligence technology. The methodology adopted to conduct the research involved a thorough literature survey on risk management, informal and formal discussions with construction practitioners to assess the extent of the problem, a questionnaire survey to evaluate the importance of global risk factors and, finally, repertory grid interviews aimed at eliciting relevant knowledge. There are several approaches to categorising risks permeating construction projects. This research groups risks into three main categories, namely organisation-specific, global and Acts of God. It focuses on global risk factors because they are ill-defined, less understood by contractors and difficult to model, assess and manage although they have huge impact on cost performance. Generally, contractors, especially in developing countries, have insufficient experience and knowledge to manage them effectively. The research identified the following groups of global risk factors as having significant impact on cost performance: estimator related, project related, fraudulent practices related, competition related, construction related, economy related and political related factors. The model was tested for validity through a panel of validators (experts) and crosssectional cases studies, and the general conclusion was that it could provide valuable assistance in the management of global risk factors since it is effective, efficient, flexible and user-friendly. The findings stress the need to depart from traditional approaches and to explore new directions in order to equip contractors with effective risk management tools

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing