Multi-sector bounded-neighbourhood model: agent segregation and optimization of environment characteristics

This article presents an approach to studying the effects of segregation using the developed multi-sector bounded-neighbourhood model. A model of the evolutionary dynamics of a community consisting of a local (natives) and external population (migrants) interacting in an artificial socio-economic system is proposed, in which the key sectors of the economy are highlighted: mining of raw materials (the primary sector, which attracts mainly migrants), the manufacturing sector (the secondary sector, which attracts mainly indigenous people), and the sphere of low-tech and high-tech services (the tertiary and quaternary sectors of the economy, which attract migrants and indigenous people, respectively). Formation of jobs in these sectors of the economy is carried out centrally using the previously proposed fuzzy clustering algorithm. Simulation experiments were carried out and the effects of segregation were investigated due to the desire of agents to search for the most preferable jobs in a bounded-neighbourhood under various scenario conditions. Using the proposed genetic algorithm, an important optimization problem was solved to maximize the GDP growth rate and minimize the level of population segregation.