Simulation of spatial population dynamics based on labor economics and multi-agent systems: a case study on a rapidly developing manufacturing metropolis

Abstract

Spatial population dynamics affects resource allocation in urban planning. Simulation of population dynamics can provide useful information to urban planning for rapidly developing manufacturing metropolises. In such a metropolis with a concentration of immigrant labor forces, individual employment choices could have a significant effect on their residential decisions. There remains a need for an efficient method, which can simulate spatial population dynamics by considering the interactions between employment and residential choices. This article proposes an agent-based model for simulation of spatial population dynamics by addressing the influence of labor market on individual residential decisions. Labor economics theory is incorporated into a multi-agent system in this model. The long-term equilibrium process of labor market is established to define the interactions between labor supply and labor demand. An agent-based approach is adopted to simulate the economic behaviors and residential decisions of population individuals. The residential decisions of individuals would eventually have consequences on spatial population dynamics. The proposed model has been verified by the spatial dynamics simulation (2007 to 2010) of Dongguan, an emerging and renowned manufacturing metropolis in the Pearl River Delta, China. The results indicate that the simulated population size and spatial distribution of each town in Dongguan are close to those obtained from census data. The proposed model is also applied to predict spatial population dynamics based on two economic planning scenarios in Dongguan from 2010 to2015. The predicted results provide insights into the population dynamics of this fast-growing region.

Keywords:

• labor economics
• agent-based model
• simulation
• spatial population dynamics
• Dongguan

Acknowledgment

This study was supported by the National Basic Research Program of China (973 Program) (Grant No. 2011CB707103), the National Natural Science Foundation of China (Grant No. 41171308), A Foundation for the Author of National Excellent Doctoral Dissertation of PR China (Grant No. 3149001), the International Collaborative Program of Science and Technology of Guangzhou Municipal Bureau of Science and Information Technology (Grant No. 2012J5100044), and the National Natural Science Foundation of China (Grant No. 41001048).