With the rapid development of the digital economy, digital service trade has become a significant driver of economic growth for various countries. In the context of globalization, enhancing a nation’s competitiveness in the international market is particularly vital. Therefore, establishing an effective competitiveness evaluation model and optimizing related policy pathways are urgent tasks at hand. This paper presents a mathematical model based on an improved genetic algorithm designed to comprehensively assess the international competitiveness of digital service trade across different countries. The model takes into account multiple factors, including cost, efficiency, technological level, and innovation capability, and optimizes the selection of policy comparison paths through a fitness function. Through simulation analysis of the competitiveness of digital service trade in various nations, this paper explores the impact of different policies and their optimization strategies. The findings indicate that the improved genetic algorithm can effectively enhance the accuracy of competitiveness evaluation for digital service trade, providing a scientific basis for policy formulation. Furthermore, the paper emphasizes that policy innovation and technological advancement are key factors in boosting the competitiveness of digital service trade. Countries should increase investment in these two areas to achieve higher levels of economic growth and strengthen their international trade competitiveness. This approach will better adapt to changes in the global market and promote sustainable economic development for nations.