From research project to research portfolio: Meeting scale and complexity
Investment in research and innovation faces increasing scrutiny in countries that already do a lot of it. How much investment is optimal? How can we tell if and when our research activities offer less value for the dollar spent on them? How can we ensure that the benefits of investments accrue to those who incur the cost?
Research of trends of the development of the scientific bibliometric information in distributed databases as an application of the Kondratyev’s theory of cyclic dynamics of the socio-economic systems was done in this work. A structural analysis of resources of the intellectual information space was fulfilled and an algorithm for forecasting of the development of scientific and technological trends which basis on the analysis of equidistant time series’ distribution of patents in databases was designed. Indicators, which are reflecting the development of the potential of technology trends and the methodology for calculating ones, were built and represented.
Article is devoted to problem solving of a lack of capital resources for realization of project portfolio on basis of revealed laws in financing, budgeting and capital rationing system in the company.
The companies that are IT-industry leaders perform from several tens to several hundreds of projects simultaneously. The main problem is to decide whether the project is acceptable to the current strategic goals and resource limits of a company or not. This leads firms to an issue of a project portfolio selection; therefore, the challenge is to choose the subset of all projects which satisfy the strategic objectives of a company in the best way. In this present article we propose the multi-objective mathematical model of the project portfolio selection problem, defined on the fuzzy trapezoidal numbers. We provide an overview of methods for solving this problem, which are a branch and bound approach, an adaptive parameter variation scheme based on the epsilon-constraint method, ant colony optimization method and genetic algorithm. After analysis, we choose ant colony optimization method and SPEA II method, which is a modification of a genetic algorithm. We describe the implementation of these methods applied to the project portfolio selection problem. The ant colony optimization is based on the max min ant system with one pheromone structure and one ant colony. Three modification of our SPEA II implementation were considered. The first adaptation uses the binary tournament selection, while the second requires the rank selection method. The last one is based on another variant of generating initial population. The part of the population is generated by a non-random manner on the basis of solving a one-criterion optimization problem. This fact makes the population more strongly than an initial population, which is generated completely by random.
The world is changing. From shopping malls to transport terminals, aircraft to passenger ships, the infrastructure of society has to cope with ever more intense and complex flows of people. Today, more than ever, safety, efficiency and comfort are issues that must be addressed by all designers. The World Trade Centre disaster brought into tragic focus the need for well-designed evacuation systems. The new regulatory framework in the marine industry, acknowledges not only the importance of ensuring that the built environment is safe, but also the central role that evacuation simulation can play in achieving this.
An additional need is to design spaces for efficiency – ensuring that maximum throughput can be achieved during normal operations – and comfort – ensuring that the resulting flows offer little opportunity for needless queuing or excessive congestion. These complex demands challenge traditional prescriptive design guides and regulations. Designers and regulators are consequently turning to performance-based analysis and regulations facilitated by the new generation of people movement models.
Already enough long time the Russian economy operates in rather stable macroeconomic conditions provided by existence of oil and gas "pillow". Even world financial crisis of 2008- 2009 didn't lead to long and essential falling of the prices for oil that allowed Russia to continue the policy on stabilizing the main macroeconomic indicators. At the same time, proclaimed by Russian Government, course on modernization of economy (actually proclaimed at the beginning of the 2000s, but not just at recent 4 years) should cause definite changes in national innovative system during this period and in these favorable financial conditions. In this article we will consider how the technological profile of the Russian innovative system has been changed and what forms of innovative behavior of key economic agents were established.
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.