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In this paper, we discuss the procedure for finding nominal trajectories of the planar five-link bipedal robot with point contact. To this end we use a virtual constraints method that transforms robot’s dynamics to a lowdimensional zero manifold; we also use a nonlinear optimization algorithms to find virtual constraints parameters that minimize robot’s cost of transportation. We analyzed the effect of the degree of Bezier polynomials that approximate the virtual constraints and continuity of the torques on the cost of transportation. Based on numerical results we found that it is sufficient to consider polynomials with degrees between five and six, as further increase in the degree of polynomial results in increased computation time while it does not guarantee reduction of the cost of transportation. Moreover, it was shown that introduction of torque continuity constraints does not lead to significant increase of the objective function and makes the gait more implementable on a real robot.

We propose a two step procedure for finding minimum of the considered optimization problem with objective function in the form of cost of transportation and with high number of constraints. During the first step we solve a feasibility problem: remove cost function (set it to zero) and search for feasible solution in the parameter space. During the second step we introduce the objective function and use the solution found in the first step as initial guess. For the first step we put forward an algorithm for finding initial guess that considerably reduced optimization time of the first step (down to 3–4 seconds) compared to random initialization. Comparison of the objective function of the solutions found during the first and second steps showed that on average during the second step objective function was reduced twofold, even though overall computation time increased significantly.

Based on the time-discrete model, we study the effect of selective proportional harvesting on the population dynamics with age and sex structure. When constructing the model, we assume that the population birth rate depends on the ratio of the sexes and the number of formed pairs. The regulation of population growth is carried out by limiting the juvenile’s survival when the survival of immature individuals decreases with an increase in the numbers of sex and age classes. We consider cases where the harvest is carried out only from a younger age class or from a group of mature females or males. We find that the harvesting of males or females at the optimal level is responsible for changing the ratio of females to males (taking into account the average size of the harem). We show that the maximum number of harvested males is achieved either at such a harvest rate when their excess number is withdrawn and the balance of sexes is established or at such an optimal catch quota at which the sex ratio is shifted towards breeding females. Optimal female harvesting, in which the highest number of them are taken, either maintains a preexisting shortage of adult males or leads to an excess of males or the fixing of a sex balance. We find that, depending on the population parameters for all considered harvesting strategies, the hydra effect can observe, i. e., the equilibrium size of the exploited sex and age-specific group (after reproduction) can increase with the growth of harvesting intensity. The selective harvesting, due to which the hydra effect occurs, simultaneously leads to an increase remaining population size and the number of harvested individuals. At the same time, the size of the exploited group after reproduction can become even more than without exploitation. Equilibrium harvesting with the optimal harvest rate that maximizes yield leads to a population size decrease. The effect of hydra is at lower values of the catch quota than the optimal harvest rate. At the same time, the consequence of the hydra effect may be a higher abundance of the age-sex group under optimal exploitation compared to the level observed in the absence of harvesting.

This paper demonstrates the advantages of using artificial intelligence algorithms for the design of experiment theory, which makes possible to improve the accuracy of parameter identification for an elastostatic robot model. Design of experiment for a robot consists of the optimal configuration-external force pairs for the identification algorithms and can be described by several main stages. At the first stage, an elastostatic model of the robot is created, taking into account all possible mechanical compliances. The second stage selects the objective function, which can be represented by both classical optimality criteria and criteria defined by the desired application of the robot. At the third stage the optimal measurement configurations are found using numerical optimization. The fourth stage measures the position of the robot body in the obtained configurations under the influence of an external force. At the last, fifth stage, the elastostatic parameters of the manipulator are identified based on the measured data.

The objective function required to finding the optimal configurations for industrial robot calibration is constrained by mechanical limits both on the part of the possible angles of rotation of the robot’s joints and on the part of the possible applied forces. The solution of this multidimensional and constrained problem is not simple, therefore it is proposed to use approaches based on artificial intelligence. To find the minimum of the objective function, the following methods, also sometimes called heuristics, were used: genetic algorithms, particle swarm optimization, simulated annealing algorithm, etc. The obtained results were analyzed in terms of the time required to obtain the configurations, the optimal value, as well as the final accuracy after applying the calibration. The comparison showed the advantages of the considered optimization techniques based on artificial intelligence over the classical methods of finding the optimal value. The results of this work allow us to reduce the time spent on calibration and increase the positioning accuracy of the robot’s end-effector after calibration for contact operations with high loads, such as machining and incremental forming.

New Asynchronous Differential Evolution algorithm is used to determine the parameters of microscopic optical potential of elastic pion scattering on ²⁸Si, ⁵⁸Ni and ²⁰⁸Pb nuclei at energy 130, 162 and 180 MeV.

The study is based on a three-dimensional hydrodynamic global climate coupled model, including ocean model with real depths and continents configuration, sea ice evolution model and energy and moisture balance atmosphere model. Aerosol concentration from the year 2010 to 2100 is calculated as a controlling parameter to stabilize mean year surface air temperature. It is shown that by this way it is impossible to achieve the space and seasonal uniform approximation to the existing climate, although it is possible significantly reduce the greenhouse warming effect. Climate will be colder at 0.1–0.2 degrees in the low and mid-latitudes and at high latitudes it will be warmer at 0.2–1.2 degrees. The Pareto frontier is investigated and visualized for two parameters — atmospheric temperature mean square deviation for the winter and summer seasons. The Pareto optimal amount of sulfur emissions would be between 23.5 and 26.5 TgS/year.

This paper studies minimum volume elastoplastic bodies. One part of the boundary of every reviewed body is fixed to the same space points while stresses are set for the remaining part of the boundary surface (loaded surface). The shape of the loaded surface can change in space but the limit load factor calculated based on the assumption that the bodies are filled with elastoplastic medium must not be less than a fixed value. Besides, all varying bodies are supposed to have some type of a limited volume sample manifold inside of them.

The following problem has been set: what is the maximum number of cavities (or holes in a two-dimensional case) that a minimum volume body (plate) can have under the above limitations? It is established that in order to define a mathematically correct problem, two extra conditions have to be met: the areas of the holes must be bigger than the small constant while the total length of the internal hole contour lines within the optimum figure must be minimum among the varying bodies. Thus, unlike most articles on optimum design of elastoplastic structures where parametric analysis of acceptable solutions is done with the set topology, this paper looks for the topological parameter of the design connectivity.

The paper covers the case when the load limit factor for the sample manifold is quite large while the areas of acceptable holes in the varying plates are bigger than the small constant. The arguments are brought forward that prove the Maxwell and Michell beam system to be the optimum figure under these conditions. As an example, microphotographs of the standard biological bone tissues are presented. It is demonstrated that internal holes with large areas cannot be a part of the Michell system. At the same the Maxwell beam system can include holes with significant areas. The sufficient conditions are given for the hole formation within the solid plate of optimum volume. The results permit generalization for three-dimensional elastoplastic structures.

The paper concludes with the setting of mathematical problems arising from the new problem optimally designed elastoplastic systems.

The most important principle of military science and border security is the principle of concentrating the main efforts on the main directions and tasks. At the tactical level, there are many mathematical models for computing the optimal resource allocation by directions and objects, whereas at the state level there are no corresponding models. Using the statistical data on the results of the protection of the US border, an exponential type border production function parameter is calculated that reflects the organizational and technological capabilities of the border guard. The production function determines the dependence of the probability of detaining offenders from the density of border guards per kilometer of the border. Financial indicators in the production function are not taken into account, as the border maintenance budget and border equipment correlate with the number of border agents. The objective function of the border guards is defined — the total prevented damage from detained violators taking into account their expected danger for the state and society, which is to be maximized. Using Slater's condition, the solution of the problem was found — optimal density of border guard was calculated for the regions of the state. Having a model of resource allocation, the example of the three border regions of the United States has also solved the reverse problem — threats in the regions have been assessed based on the known allocation of resources. The expected danger from an individual offender on the US-Canada border is 2–5 times higher than from an offender on the US-Mexican border. The results of the calculations are consistent with the views of US security experts: illegal migrants are mostly detained on the US-Mexican border, while potential terrorists prefer to use other channels of penetration into the US (including the US-Canadian border), where the risks of being detained are minimal. Also, the results of the calculations are consistent with the established practice of border protection: in 2013 the number of border guards outside the checkpoints on the US-Mexican border increased by 2 times compared with 2001, while on the American-Canadian border — 4 times. The practice of border protection and the views of specialists give grounds for approval of the verification of the model.

The traditional approach to computing optimal game strategies of firms on oligopolistic markets and of indicators of such markets consists in studying linear dynamical games with quadratic criteria and solving generalized matrix Riccati equations.

The other approach proposed by the author is based on methods of operational calculus (in particular, Z-transform). This approach makes it possible to achieve economic meaningful decisions under wider field of parameter values. It characterizes by simplicity of computations and by necessary for economic analysis visibility. One of its advantages is that in many cases important for economic practice, it, in contrast to the traditional approach, provides the ability to make calculations using widespread spreadsheets, which allows to study the prospects for the development of oligopolistic markets to a wide range of professionals and consumers.

The article deals with the practical aspects of determining the optimal Nash–Cournot strategies of participants in oligopolistic markets on the basis of operational calculus, in particular the technique of computing the optimal Nash–Cournot strategies in Excel. As an illustration of the opportinities of the proposed methods of calculation, examples close to the practical problems of forecasting indicators of the markets of high-tech products are studied.

The results of calculations obtained by the author for numerous examples and real economic systems, both using the obtained relations on the basis of spreadsheets and using extended Riccati equations, are very close. In most of the considered practical problems, the deviation of the indicators calculated in accordance with the two approaches, as a rule, does not exceed 1.5–2%. The highest value of relative deviations (up to 3–5%) is observed at the beginning of the forecasting period. In typical cases, the period of relatively noticeable deviations is 3–5 moments of time. After the transition period, there is almost complete agreement of the values of the required indicators using both approaches.

Working memory mechanisms in spiking neural networks consisting of leaky integrate-and-fire neurons with adaptive threshold and synaptic plasticity are studied in this work. Moderate size networks including thousands of neurons were explored. Working memory is a network ability to keep in its state the information about recent stimuli presented to the network such that this information is sufficient to determine which stimulus has been presented. In this study, network state is defined as the current characteristics of network activity only — without internal state of its neurons. In order to discover the neuronal structures serving as a possible substrate of the memory mechanism, optimization of the network parameters and structure using genetic algorithm was carried out. Two kinds of neuronal structures with the desired properties were found. These are neuron pairs mutually connected by strong synaptic links and long tree-like neuronal ensembles. It was shown that only the neuron pairs are suitable for efficient and reliable implementation of working memory. Properties of such memory units and structures formed by them are explored in the present study. It is shown that characteristics of the studied two-neuron memory units can be set easily by the respective choice of the parameters of its neurons and synaptic connections. Besides that, this work demonstrates that ensembles of these structures can provide the network with capability of unsupervised learning to recognize patterns in the input signal.

The creation of a virtual laboratory stand that allows one to obtain reliable characteristics that can be proven as actual, taking into account errors and noises (which is the main distinguishing feature of a computational experiment from model studies) is one of the main problems of this work. It considers the following task: there is a rectangular waveguide in the single operating mode, on the wide wall of which a technological hole is cut, through which a sample for research is placed into the cavity of the transmission line. The recovery algorithm is as follows: the laboratory measures the network parameters (S₁₁ and/or S₂₁) in the transmission line with the sample. In the computer model of the laboratory stand, the sample geometry is reconstructed and an iterative process of optimization (or sweeping) of the electrophysical parameters is started, the mask of this process is the experimental data, and the stop criterion is the interpretive estimate of proximity (or residual). It is important to note that the developed computer model, along with its apparent simplicity, is initially ill-conditioned. To set up a computational experiment, the Comsol modeling environment is used. The results of the computational experiment with a good degree of accuracy coincided with the results of laboratory studies. Thus, experimental verification was carried out for several significant components, both the computer model in particular and the algorithm for restoring the target parameters in general. It is important to note that the computer model developed and described in this work may be effectively used for a computational experiment to restore the full dielectric parameters of a complex geometry target. Weak bianisotropy effects can also be detected, including chirality, gyrotropy, and material nonreciprocity. The resulting model is, by definition, incomplete, but its completeness is the highest of the considered options, while at the same time, the resulting model is well conditioned. Particular attention in this work is paid to the modeling of a coaxial-waveguide transition, it is shown that the use of a discrete-element approach is preferable to the direct modeling of the geometry of a microwave device.