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On January 24, a famous scientist, doctor of physical and mathematical sciences, professor and laureate of the Prize of S.V. Kowalevsky Alexey Vladimirovich Borisov passed away. Alexey Vladimirovich was born and raised in Moscow. After graduating from high school, he entered the Faculty of Special Mechanical Engineering of the Bauman Moscow State Technical University. Already during his studies, Alexey Vladimirovich attends a scientific seminar at the Faculty of Mechanics and Mathematics of the Lomnosov Moscow State University, which largely determines the direction of his future research. After defending his Ph.D. thesis, Alexey Vladimirovich creates a scientific group in Izhevsk, his subsequent scientific biography is very wide: Yekaterinburg, Cheboksary, Innopolis, Dolgoprudny, Moscow. Borisov founds and heads the series of scientific journals Regular and Chaotic Dynamics, Nonlinear Dynamics, is the editor-in-chief in the journals Bulletin of Udmurt University, Computer research and modeling. The scientific heritage of A.V. Borisov is extensive, the list of publications is more than 200 works, more than 170 of which have been published in journals indexed by international databases Scopus and Web of Science. More than 10 monographs belong to him.

The article provides approaches to evolutionary modelling of synthesis of organised systems and analyses methodological problems of evolutionary computations of this kind. Based on the analysis of works on evolutionary cybernetics, evolutionary theory, systems theory and synergetics, we conclude that there are open problems in formalising the synthesis of organised systems and modelling their evolution. The article emphasises that the theoretical basis for the practice of evolutionary modelling is the principles of the modern synthetic theory of evolution. Our software project uses a virtual computing environment for machine synthesis of problem solving algorithms. In the process of modelling, we obtained the results on the basis of which we conclude that there are a number of conditions that fundamentally limit the applicability of genetic programming methods in the tasks of synthesis of functional structures. The main limitations are the need for the fitness function to track the step-by-step approach to the solution of the problem and the inapplicability of this approach to the problems of synthesis of hierarchically organised systems. We note that the results obtained in the practice of evolutionary modelling in general for the whole time of its existence, confirm the conclusion the possibilities of genetic programming are fundamentally limited in solving problems of synthesizing the structure of organized systems. As sources of fundamental difficulties for machine synthesis of system structures the article points out the absence of directions for gradient descent in structural synthesis and the absence of regularity of random appearance of new organised structures. The considered problems are relevant for the theory of biological evolution. The article substantiates the statement about the biological specificity of practically possible ways of synthesis of the structure of organised systems. As a theoretical interpretation of the discussed problem, we propose to consider the system-evolutionary concept of P.K.Anokhin. The process of synthesis of functional structures in this context is an adaptive response of organisms to external conditions based on their ability to integrative synthesis of memory, needs and information about current conditions. The results of actual studies are in favour of this interpretation. We note that the physical basis of biological integrativity may be related to the phenomena of non-locality and non-separability characteristic of quantum systems. The problems considered in this paper are closely related to the problem of creating strong artificial intelligence.

The paper demonstrates a fractal system of thin plates connected with hinges. The system can be studied using the methods of mechanics of solids with internal degrees of freedom. The structure is deployable — initially it is close to a small diameter one-dimensional manifold that occupies significant volume after deployment. The geometry of solids is studied using the method of the moving hedron. The relations enabling to define the geometry of the introduced manifolds are derived based on the Cartan structure equations. The proof substantially makes use of the fact that the fractal consists of thin plates that are not long compared to the sizes of the system. The mechanics is described for the solids with rigid plastic hinges between the plates, when the hinges are made of shape memory material. Based on the ultimate load theorems, estimates are performed to specify internal pressure that is required to deploy the package into a three-dimensional structure, and heat input needed to return the system into its initial state.

We present the iterative algorithm that solves numerically both Urysohn type Fredholm and Volterra nonlinear one-dimensional nonsingular integral equations of the second kind to a specified, modest user-defined accuracy. The algorithm is based on descending recursive sequence of quadratures. Convergence of numerical scheme is guaranteed by fixed-point theorems. Picard’s method of integrating successive approximations is of great importance for the existence theory of integral equations but surprisingly very little appears on numerical algorithms for its direct implementation in the literature. We show that successive approximations method can be readily employed in numerical solution of integral equations. By that the quadrature algorithm is thoroughly designed. It is based on the explicit form of fifth-order embedded Runge–Kutta rule with adaptive step-size self-control. Since local error estimates may be cheaply obtained, continuous monitoring of the quadrature makes it possible to create very accurate automatic numerical schemes and to reduce considerably the main drawback of Picard iterations namely the extremely large amount of computations with increasing recursion depth. Our algorithm is organized so that as compared to most approaches the nonlinearity of integral equations does not induce any additional computational difficulties, it is very simple to apply and to make a program realization. Our algorithm exhibits some features of universality. First, it should be stressed that the method is as easy to apply to nonlinear as to linear equations of both Fredholm and Volterra kind. Second, the algorithm is equipped by stopping rules by which the calculations may to considerable extent be controlled automatically. A compact C++-code of described algorithm is presented. Our program realization is self-consistent: it demands no preliminary calculations, no external libraries and no additional memory is needed. Numerical examples are provided to show applicability, efficiency, robustness and accuracy of our approach.