There is a large body of research devoted to identifying the complexity of structures in networks. In the context of network theory, a complex network is a graph with nontrivial topological features—features that do not occur in simple networks, such as lattices or random graphs, but often occur in graphs modeling real systems. The study of complex networks is a young and active area of scientific research inspired largely by the empirical study of real-world networks, such as computer networks and logistic transport networks. Transport is of great importance for the economic and cultural cooperation of any country with other countries, the strengthening and development of the economic management system, and in solving social and economic problems. Provision of the territory with a well-developed transport system is one of the factors for attracting population and production, serving as an important advantage for locating productive forces and providing an integration effect. In this paper, we introduce a new method for quantifying the complexity of a network based on presenting the nodes of the network in Cartesian coordinates, converting to polar coordinates, and calculating the fractal dimension using the ReScaled ranged (R/S) method. Our results suggest that this approach can be used to determine complexity for any type of network that has fixed nodes, and it presents an application of this method in the public transport system.

Selection pressure, determining which individuals survive and reproduce, is traditionally regarded as an exogenous property of the environment. However, growing evidence from the Extended Evolutionary Synthesis (EES) suggests that the strength of selection can, to some extent, be modulated by the organisms themselves. In this paper, we propose a minimal game-theoretical model that formalizes the concept of endogenous selection pressure. In the model, individuals collectively determine the intensity of selection through their actions: each agent "votes" to either intensify or relax selection depending on its relative fitness rank. The aggregate outcome of these decisions defines the number of reproducers, k, which is inversely related to the overall strength of selection. We analytically derive all pure strategy Nash equilibria of the game and examine their properties. By internalizing selection as a population-level emergent variable, the framework provides a tractable formalization of key principles from the EES and offers a foundation for exploring evolutionary dynamics that arise under the presence of endogenous selection pressure.