As a result of the climate change the situation in Arctic area leads to several important consequences. On the one hand, fossil fuels can be exploited much easier than before. On the other hand, their excavation leads to serious potential threats to fishing by changing natural habitats which in turn creates serious damage to the countries’ economies. Another set of problems arises due to the extension of navigable season for shipping routes. Thus, there are already discussions on how should resources be allocated among countries. In Aleskerov and Victorova (An analysis of potential conflict zones in the Arctic Region, HSE Publishing House, Moscow, 2015) a model was presented analyzing preferences of the countries interested in natural resources and revealing potential conflicts among them. We present several areas allocation models based on different preferences over resources among interested countries. As a result, we constructed several allocations where areas are assigned to countries with respect to the distance or the total interest, or according to the procedure which is counterpart of the Adjusted Winner procedure. We consider this work as an attempt to help decision-making authorities in their complex work on adjusting preferences and conducting negotiations in the Arctic zone. We would like to emphasize that these models can be easily extended to larger number of parameters, to the case when some areas for some reasons should be excluded from consideration, to the case with ‘weighted’ preferences with respect to some parameters. And we strongly believe that such models and evaluations based on them can be helpful for the process of corresponding decision making.
The paper develops a new extension of the sequential preference condition, which leads to unique stable matching in all subpopulations, obtained by consistent restrictions of the marriage matching problem. Under the new condition, the Gale–Shapley algorithm is stable, consistent, strategy-proof, Pareto optimal for men, and Pareto optimal for women.
Explicit two-level in time and symmetric in space finite-difference schemes constructed by approximating the 1D barotropic quasi-gas-/quasi-hydrodynamic systems of equations are studied. The schemes are linearized about a constant solution with a nonzero velocity, and, for them, necessary and sufficient conditions for the L2-dissipativity of solutions to the Cauchy problem are derived depending on the Mach number. These conditions differ from one another by at most twice. The results substantially develop the ones known for the linearized Lax–Wendroff scheme. Numerical experiments are performed to analyze the applicability of the found conditions in the nonlinear formulation to several schemes for different Mach numbers.
The paper studies group-separable preference profiles. Such a profile is group-separable if for each subset of alternatives there is a partition in two parts such that each voter prefers each alternative in one part to each alternative in the other part. We develop a parenthesization representation of group-separable domain. The precise formula for the number of group-separable preference profiles is obtained. The recursive formula for the number of narcissistic group-separable preference profiles is obtained. Such a profile is narcissistic group-separable if it is group-separable and each alternative is preferred the most by exactly one voter.
We present the basic properties of the a new pattern analysis method in parallel coordinates; results of the method do not depend on the ordering of data in the original sample of objects being analyzed. We prove that clusters obtained with this method do not overlap. We also show the possibility of representing objects of one cluster in the form of monotonically increasing/decreasing functions.
We propose a model that evaluates how much a network has changed over time in terms of its structure and a set of central elements. The difference of structure is evaluated in terms of node-to-node influence using known nodes correspondence models. To analyze the changes in nodes centralities we adapt an idea of interval orders to the network theory. Our approach can be used to investigate dynamic changes in temporal networks and to identify suspicious or abnormal effects in terms of the topology and its critical members. We can also transform the stability measure to the similarity measure in order to cluster the network in some homogeneous periods. To test our model, we consider the international migration network from 1970 to 2015 and attempt to analyze main changes in migration patterns.
We propose a family of new measures for edge importance estimation. We focus on weighted directed networks where weights indicate the intensity of connections between nodes. We reward edges that increase node-tonode influence compared to direct connections between them. This approach allows to reveal hidden channels of the influence in networks. We apply the proposed model to food export/import networks in order to elucidate the most important trading relations. We compare the results with edge-betweenness centrality and investigate the interdependence between edge importance and centrality measures of corresponding source and sink nodes. The results are provided in dynamic.
The Central Banks discuss bank recapitalization arrangements. Markup to capital is needed because the current Basel approach is insensitive to some risks. As the Basel Committee moves from comprehensive risk modelling towards a revised, simplified, standardised approach, where one-two triggers measure risk, banking regulators increase demand for a capital add-on to meet unaccounted risks. The paper suggests the add-on estimates for the joint effect of the concentration and PD-LGD correlation risks leaving other unaccounted ones out-of-scope. The previous studies estimated add-ons for each risk separately. We show their joint impact on capital can be higher up to 5.3 times than the sum of two taken apart. Then previous results do not provide sufficient capital for a bank. We obtain that Basel underestimates the joint risk in 1.9 times on average. We expect that our contribution will be useful at least but not last for specialised lending (e.g. real estate and project finance), where the joint effect of concentration and PD-LGD correlation risks is the most observable.
An entropy dissipative spatial discretization has recently been constructed for the multidimensional gas dynamics equations based on their preliminary parabolic quasi-gasdynamic (QGD) regularization. In this paper, an explicit finite-difference scheme with such a discretization is verified on several versions of the 1D Riemann problem, both well-known in the literature and new. The scheme is compared with the previously constructed QGD-schemes and its merits are noticed. Practical convergence rates in the mesh $L^1$-norm are computed. We also analyze the practical relevance in the nonlinear statement as the Mach number grows of recently derived necessary conditions for $L^2$-dissipativity of the Cauchy problem for a linearized QGD-scheme.
We present the basic properties of the a new pattern analysis method in the system of parallel coordinates; results of the method do not depend on the ordering of data in the original sample of objects being analyzed. We prove that clusters obtained with this method do not overlap. We also show the possibility of representing objects of one cluster in the form of monotonically increasing/decreasing functions.
The assembly process is extremely complex for aircraft and its management requires to address numerous optimization problems related to the assignment of tasks to workstations, staffing problem for each workstation and finally the assignment of tasks to operators at each workstation. This paper treats the latter problem dealing with the assignment of tasks to operators under ergonomic constraints. The problem of optimal tasks scheduling in aircraft assembly line is modelled as Resource-Constrained Project Scheduling Problem (RCPSP). The objective of this research is to assign tasks to operators and to find an optimal schedule of task processing under economic and ergonomic constraints. Two different models to solve this problem are presented and evaluated on an industrial case study.
The article is dedicated to the method of aggregation of financial analysts’ recommendations in the framework of the evidence theory. This method considered on the example of Russian stock market and the quality of the obtained results was compared with the classical consensus forecast. It is shown that the combination rules, which are widely developed in the theory of evidence, allow aggregating the recommendations of analysts taking into account the historical reliability of information sources, the nature of the taken decisions (pessimism-optimism), the conflict between forecasts and recommendations, etc. In most cases it turned out that, obtained aggregated forecasts are more accurate than consensus forecast.
The Resource-Constrained Project Scheduling Problem (RCPSP) is considered. This problem is NP-hard in strong sense (Garey and Johnson 1975). In this paper, a new polynomial-time approach is developed to find an upper bound on resource consumption. This bound can be also used to calaculate a lower bound for makespan. The procedure also helps to increase the efficiency of existed propagators and to improve constraint programming model performances by tightening decision variables domains.
This paper presents the results of volatility forecasting for indices of the Russian stock market using existing and developed by the authors fuzzy asymmetric GARCH-models. These models consider various switching functions which are taking into account the positive and negative shocks and are built using the tools of fuzzy numbers. Furthermore, in some models there are used switching functions that consider expert macroeconomic information. It was shown that fuzzy asymmetric GARCH-models provide a more accurate prediction of volatility than similar crisp models.
This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing the machine learning theory. The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches. The collection is divided in three parts. The first part bridges the past and the present. Its main contents relate to the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essays by a friend, a student, and a colleague.