Simulation study on the urban-rural integration circulatory mechanism system in China
Based on system dynamics model and multi-objective genetic algorithm
Bibliographic Data
| ID | 6455804 |
|---|---|
| Authors | Gaoyang Liang (0009-0005-4203-6313), Mengyao Xing, Jian-Qiang Zhao (0000-0003-2398-3081) |
| Year | 2025 |
| Volume | 10 |
| Pages | 101074-101074 |
| Publication date | 2025-08-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Futures (JOURNAL) |
| Journal identifiers | ISSN: 2666-1888 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.sftr.2025.101074 |
| OpenAlex | W4413274521 |
| Language | EN |
| Citations received | 1 |
| References cited | 125 |
Existing academic research on China’s urban-rural integration lacks a comprehensive exploration that integrates “factors and pathways” while providing a dynamic depiction of how different driving forces influence the urban-rural integration process. To bridge this gap, this study constructs a “Theoretical Model of the Urban-Rural Integration Circulatory Mechanism” based on three core driving forces—market circulation, public service circulation, and information technology circulation—by reviewing relevant literature and clarifying the roles and interrelationships of these factors in economic, social, spatial, ecological, and population integration. Utilizing system dynamics principles, this study designs a stock-flow model and a causal loop diagram of the urban-rural integration circulatory system, performing in-depth simulation analyses including baseline scenarios, endogenous driving force scenarios (stimulating market circulation), exogenous driving force scenarios (stimulating public service circulation), and fundamental driving force scenarios (stimulating information technology circulation) to evaluate the model’s sensitivity and dynamics. The results indicate that all three driving forces significantly enhance the overall level of urban-rural integration, with the most substantial improvements observed in economic and social integration. Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. This research contributes to a deeper theoretical understanding of the urban-rural integration mechanism and provides preliminary insights that may serve as a reference for promoting balanced and sustainable urban-rural development in China
Biological system · Biology · China · Dynamics (music · Genetic algorithm · Geography · Machine learning · Mechanism (biology · Model system · Physics · Simulation · System dynamics · Computer Science · Urban Transport and Accessibility · Artificial Intelligence
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |