Optimization of Vehicle-Cargo Matching Regarding the Income of Suppliers and Soft Matching Constraints

The significant income gap among suppliers on vehicle-cargo matching platforms poses a looming threat of supplier loss. Furthermore, the persistently low success rate in matching cargo with suitable suppliers reinforces this problem, leading to a decline in both supplier and customer numbers. These challenges have a profound impact on the operational efficiency of these platforms. To balance the suppliers’ income and enhance the matching success rate, this paper proposes a novel model that takes into account the income of suppliers while incorporating the concept of soft matching constraints. When a customer's request cannot be immediately fulfilled, a suboptimal matching solution is proposed to the customer. The customer is then given the choice to either accept this recommendation or opt to wait for the subsequent round of matching. To balance the suppliers’ income, suppliers with lower income have high priority in matching, thereby creating a fairer and more equitable matching environment.