Abstract

This study addresses the critical challenge of green port construction in China, with a focus on the underutilized potential of shore power technology, through a computational lens. By establishing an evolutionary game model that captures the intricate dynamics among ports, shipping companies, and government agencies, we introduce a computational framework that utilizes advanced data analytics, network simulations, and optimization algorithms to evaluate policy incentives and their efficacy. The heart of our analysis lies in the deployment of network simulation tools and predictive analytics, which facilitate a deep dive into the operational dynamics and strategy adaptations within the tripartite system. Our findings underscore the pivotal role of government subsidies, quantitatively determined through optimization algorithms, in influencing the evolutionary path towards sustainable port operations. The research demonstrates that a carefully calibrated subsidy regime, informed by simulation outcomes and data-driven insights, can significantly boost the adoption of shore power technologies among ports and shipping companies, nurturing a symbiotic relationship that accelerates green construction efforts. Furthermore, the study leverages computational algorithms to simulate initial game scenarios, revealing how the presence of shore power infrastructure and technology-ready ships can catalyze a cooperative push towards environmental goals. Through a comprehensive computational approach, including the use of mathematical modeling and the analysis of vast datasets, the paper highlights the transformative power of policy interventions guided by computational intelligence. The conclusions drawn not only emphasize the necessity for targeted government action but also showcase the potential of computer science methodologies in crafting and implementing effective environmental policies, offering a novel pathway to expedite the green transformation of China’s maritime infrastructure.

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