Имитационная модель поведения толпы в среде разработки AnyLogic
Development of a phenomenological approach to simulation of the human crowd behavior is presented in the paper. We consider continuous stochastic agent-based model of human behavior in a confined space with a given geometry. By analogy with the Antonini’s model, a decision making system of an agent based on an analysis of the surrounding space was introduced. The agent based model allowing to investigate the dynamics of agents taking into account ”effect of crowd” at various scenarios, in particular, in the conditions of extreme situations, in the presence of effects of “crowd crush” and “turbulence” and others effects was created in the simulation system AnyLogic.
This article describes optimization of a multimodal passenger traffic system. The optimization method used is simulation modeling. The service level indicators, costs and financial indicators when changing configurations of the system are analyzed.
The importance of strategic management today is unquestionable. However, when strategizing the organization is often regarded as a single whole, differences in aims and areas of operation of its parts not being considered. This approach works for many organizations, but in the case of a distributed structure its parts may function in the markets which have different requirements, competition intensity and qualification of consumers. Besides, the departments of that organization may have different levels of development. In our present work we do not consider the whole range of distributed organizations, but concentrate on universities, as they have common characteristics with commercial organizations and, at the same time, are very specific in their rules and areas of development. We focus on developing a new modeling method for decision support while designing a balanced hierarchical strategy for distributed universities. This implies beginning from the strategy for the whole organization and moving on to development of individual strategies for its departments. Thus, the proposed method contains two parts: a sub-method to develop departmental strategies and a sub-method to calculate interaction among departments.
This article describes the proposed structure and semantics of the model which can be used in the both of sub-methods.
The purpose of developing a cognitive model has been defined as the construction and analysis of simulation models improve interaction between government and business. In line with this objective has been hypothesized that an increase in the efficiency of interaction between business and government increased the values of competition in politics and economics, which in turn are directly related to each other. The latter is not in doubt, since the state of competition in the economy is inextricably linked to the legislative machinery of antitrust restrictions, by which representative bodies suppress or support unfair competition.
Authors provide the substantiation of logistic profitability indicator introduction for problem-solving concern the evaluation of logistic system performance, incl. inventory management system.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.