Multisector Bounded-Neighborhood Model: Agent Segregation and Optimization of Environment’s Characteristics
An approach is presented to study the effects of segregation using the developed multisector bounded-neighborhood model. A model of the evolutionary dynamics of a community consisting of local (indigenous) and external (migrants) populations interacting in an artificial socioeconomic system is proposed, in which the key sectors of the economy are identified: the extraction of raw materials (primary sector, attracting mainly migrants), the manufacturing sector (secondary sector attracting predominantly indigenous people), and low-tech and high-tech services (tertiary and quaternary sectors of the economy attracting migrants and indigenous people, respectively). The formation of jobs in these sectors of the economy is carried out centrally using the previously proposed fuzzy clustering algorithm. Simulation experiments are carried out, and the effects of segregation due to the desire of agents to search for the most desirable jobs in a bounded neighborhood under various scenario conditions are studied. Using the proposed genetic algorithm, an important optimization problem is solved to maximize GDP growth rates and minimize the level of the population’s segregation.