Модели управления финансовыми ресурсами в логистике в условиях неопределенности и риска
Current article considers the financial management models of the output expansion and switching to the renowned production program in the conditions of uncertainty and risks. It is assumed that limited amount of capital, intermediate credit as well as long-term loan, are used for the sourcing of production program computed. Posed models can be used in one-period interval as well as in dynamics.
The paper presents a formalism and a tool for modelling and analysis of distributed real-time systems of mobile agents. For that we use a time extension of our Resource Driven Automata Nets (TRDA-nets) formalism. A TRDA-net is a two-level system. The upper level represents distributed environment locations with a net of active resources. On the lower level agents are modeled by extended finite state machines, asynchronously consuming/producing shared resources through input/output system ports (arcs of the system net). We demonstrate modelling facilities of the formalism and show that specific layers of TRDA-nets can be translated into Timed Automata, as well as into Time Petri nets, thus TRDA-nets integrate merits of both formalisms.
These are the proceedings of the International Workshop on Petri Nets and Software Engineering (PNSE’13) and the International Workshop on Modeling and Business Environments (ModBE’13) in Milano, Italy, June 24–25, 2013. These are co-located events of Petri Nets 2013, the 34th international conference on Applications and Theory of Petri Nets and Concurrency.
PNSE'13 presents the use of Petri Nets (P/T-Nets, Coloured Petri Nets and extensions) in the formal process of software engineering, covering modelling, validation, and veriﬁcation, as well as their application and tools supporting the disciplines mentioned above.
ModBE’13 provides a forum for researchers from interested communities to investigate, experience, compare, contrast and discuss solutions for modeling in business environments with Petri nets and other modeling techniques.
Active vocabulary for business English students based on the business coursebook "Market Leader". The focus is on the development and mastering of business English active vocabulary for the Business Studies.
Supply chain management is rather new scientific field that reflects the concept of integrated business planning. This concept should be experts and practitioners in logistics and strategic management. Today, integrated planning to become a reality thanks to the development of information technology and computer technology. At the same time to achieve a competitive advantage is not enough high-speed, low-cost data transfer process. In order to effectively apply information technology tools necessary to develop a quantitative analysis of the effectiveness of supply chain management. The mam element of this tool are optimization models that reveal the complex interactions, the wave and the synergies that arise in supply chain management. In this article we consider one of the classes of such models - the so-called dynamic models of conveyor systems, processing of applications.
Uncertainty is a concept associated with data acquisition and analysis, usually appearing in the form of noise or measure error, often due to some technological constraint. In supervised learning, uncertainty affects classification accuracy and yields low quality solutions. For this reason, it is essential to develop machine learning algorithms able to handle efficiently data with imprecision. In this paper we study this problem from a robust optimization perspective. We consider a supervised learning algorithm based on generalized eigenvalues and we provide a robust counterpart formulation and solution in case of ellipsoidal uncertainty sets. We demonstrate the performance of the proposed robust scheme on artificial and benchmark datasets from University of California Irvine (UCI) machine learning repository and we compare results against a robust implementation of Support Vector Machines.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.