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In order to improve the performance of production systems, companies consider the optimization of the flow line configuration. However, the material supply of the flow line exerts a strong influence on the output of the production system since material shortages impede the flow of workpieces through the flow line. Simultaneously, the configuration of the flow line determines the demand for material. Consequently, the mutual interdependence between the material supply and the flow line has to be considered in order to balance a sufficient material supply of the flow line avoiding material shortages as well as excessive material inventory and handling effort. We provide integrated approaches for the evaluation and optimization of stochastic flow lines with limited material supply. Thereby, we make use of several evaluation methods as Markov chain approaches, aggregation and decomposition approaches as well as linear programming. Further, we model open and closed queuing networks in continuous and discrete time. Hence, we present exact and approximate approaches that allow us to study the effects in several stochastic production systems with limited material supply.
Measuring the degree of association between random variables is a task inherent in many practical applications such as risk management and financial modeling. Well-known measures like Spearman's rho and Kendall's tau can be expressed in terms of the underlying copula only, hence, being independent of the underlying univariate marginal distributions. Opposed to these classical measures of association, mutual information, which is derived from information theory, constitutes a fundamentally different approach of measuring association. Although this measure is likewise independent of the univariate margins, it is not a functional of the copula but of the corresponding copula density. Besides th...
This book provides a comprehensive analysis of the rules governing the taxation of permanent establishments as implemented in the OECD Model Tax Convention and German national tax law. Deviations between the OECD approach and the German approach are identified and modifications to the rules as a result of the Base Erosion and Profit Shifting (BEPS) project are examined. Moreover, challenges imposed to the PE concept as a result of the digitalisation of the economy are identified and discussed. Against this background, the Pillar One Blueprint proposing a long-term solution to overcome the tax challenges arising from the digitalisation of the economy is presented and assessed against widely accepted overarching principles of tax policy.
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Michael C. Münnix analyses the statistical dependencies in financial markets and develops mathematical models using concepts and methods from physics. The author focuses on aspects that played a key role in the emergence of the recent financial crisis: estimation of credit risk, dynamics of statistical dependencies, and correlations on small time-scales. He visualizes the findings for various large-scale empirical studies of market data. The results give novel insights into the mechanisms of financial markets and allow conclusions on how to reduce financial risk significantly.
A project planning and decision support model is developed and applied to identify and reduce risk and uncertainty in deconstruction project planning. It allows calculating building inventories based on sensor information and construction standards and it computes robust project plans for different scenarios with multiple modes, constrained renewable resources and locations. A reactive and flexible planning element is proposed in the case of schedule infeasibility during project execution.
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