Synergistic Integration of Auction-Based Game Theory and TSP for Logistics Efficiency in 2025: A Chinese Case Study

Background: As global trade networks continue to evolve, China has emerged as one of the most critical logistics epicenters worldwide. Rapid developments in infrastructure, technological innovation, and e-commerce have made efficient logistics a cornerstone of competitive advantage. This paper presents a methodological framework that integrates auction-based game theory mechanisms with the Traveling Salesman Problem (TSP) to address carrier selection and cargo-consolidation strategies in China’s freight sector. Special emphasis is placed on the year 2025, where continued urbanization, digitization, and heightened consumer expectations demand novel optimization techniques. Methods: Six major logistics centers in China (Shanghai, Beijing, Guangzhou, Shenzhen, Chengdu, and Wuhan) are analyzed as potential consolidation hubs for 12 designated supplier locations spread across multiple provinces. We employ a dual approach: (1) a game-theoretic auction mechanism ensures cost-competitive carrier selection based on dynamic regional tariffs, and (2) a TSP-based algorithm is used to optimize routing in scenarios with heterogeneous fleet characteristics and variable fuel costs. Results: Using distance data and region-specific cost parameters, we demonstrate significant monthly savings (over 15% reduction) when shifting to an optimized, integrated system. Calculations show how synergy between proper hub assignment and combinatorial route optimization yields robust improvements in both cost-efficiency and service speed. Beyond numerical gains, the model exhibits adaptability to real-world constraints such as capacity limits, seasonality, and fluctuating energy prices. Conclusions: The findings underscore the transformative potential of combining game theory with classical optimization for China’s logistics sector in 2025. By choosing strategically located consolidation centers and leveraging auction-driven pricing, stakeholders reduce redundant routing, thus lowering carbon emissions and operational expenditure. This integrated blueprint can be generalized to other rapidly expanding markets, supporting data-driven managerial decisions in a complex, evolving logistics landscape.