Coordinating socio-economic development with coastal environmental recovery is a critical challenge in rapidly urbanizing coastal regions. Few studies quantitatively integrate industrial restructuring, population dynamics, and environmental outcomes within a unified optimization framework. This study develops an Agent-Based Optimization Model of Land–Sea Processes Coupled with Socio-Economic Dynamics (ABO-LSED) within the Driver-Pressure-State-Impact-Response (DPSIR) structure to jointly optimize development drivers and regulatory responses for improved environmental outcomes. The model incorporates a pollution intensity (PI) structure as an allocation principle, deriving region-specific integrated indicators (IIs) to guide differentiated adjustments in PI reduction, sectoral growth, and population distribution across ten districts of Qingdao, China. Simulation results show that the optimization approach reduces the time required to achieve seawater quality targets from 26 to 13 years, while maintaining an average annual GDP growth rate of approximately 7%. Structural adjustments include a shift from higher to lower-intensity sectors and a moderated urbanization rate. These findings indicate that environmental recovery and economic growth can be achieved simultaneously when intensity reduction, structural transformation, and spatial redistribution are coordinated within the proposed framework. This study offers a quantitative basis for regionally differentiated policy design and provides a transferable strategy for other coastal regions.
Liu et al. (2026) studied this question.