Although central place theory has been proposed for a long time, empirical research and planning practices on central place systems in the real world under the complex multi-factor interactions are difficult to carry out. Conventional simulation-based research methods use linear programming technique to derive and investigate central place systems through optimizing certain objective functions. But their limitations on model complexity restrict their further application in empirical research and practice. Multi-agent technology provides a new perspective. This paper proposes a multi-agent retail spatial structure simulation system, which can derive structural distributions of shopping centers through simulating the behavior of shopping centers and consumers. The shopping centers in the simulation system have three levels and can adjust locations and service levels according to the revenues. Consumers generate different levels of shopping needs periodically and choose shopping centers based on travel distance. The simulation process starts with a number of shopping centers. After recursively simulating the behavior and interactions of centers and consumers, equilibrium is reached with the distributions of shopping center levels and locations emerged. As a validation of the system, simulations are carried out on five typical scenarios of consumer spatial distribution, including even distribution, single-center distribution, satellite distribution, grouped distribution, and belt distribution. Results show the system is stable with reasonable shopping center systems generated.
ZHUWei, WANG De
. Multi-agent Based Simulation of Retail Spatial Structure[J]. Acta Geographica Sinica, 2011
, 66(6)
: 796
-804
.
DOI: 10.11821/xb201106008
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