Abstract: Under the context of contract farming, the agricultural production system is characterized by a large number of smallholder farmers, low output per batch, and high-frequency production cycles. Meanwhile, increasingly diversified customer service demands and insufficient coordination among transportation entities jointly lead to high logistics costs and low operational efficiency in agricultural product distribution. Existing studies mainly focus on single-entity or independent routing optimization, which are insufficient to capture the coupling relationship between routing decisions and profit allocation in multi-entity collaborative transportation. To address this gap, this paper takes a logistics alliance composed of multiple processing enterprises as the research object and investigates the vehicle routing optimization, cost allocation, and farmers’ income changes under a collaborative transportation mode. Considering both pickup and delivery processes, a two-stage collaborative vehicle routing model is developed. The multi-enterprise collaboration problem is further transformed into a unified optimization framework consisting of 2ⁿ-1 sub-alliance routing problems. In the solution approach, k-means clustering is first applied to partition customers and reduce problem complexity. Then, an Adaptive Large Neighborhood Search (ALNS) algorithm is employed to optimize vehicle routes. Subsequently, the Shapley value method is used to fairly allocate transportation costs among alliance members. Based on this, a farmers’ income function is constructed to analyze income variations under different transportation modes. To validate the proposed model, a case study based on real-world data from Pingdu City, Qingdao, is conducted. The results show that collaborative transportation can significantly improve system performance, reducing logistics costs by 23.01%-40.26%, increasing product prices by 25.96%, enhancing farmers’ income by 56.72%, and improving customer satisfaction by 56.67%. Sensitivity analysis further demonstrates that the model maintains strong robustness under varying vehicle capacities, cost parameters, and supply-demand structures. The findings indicate that, in the context of contract farming, multi-entity collaborative transportation is not only an effective approach to reducing logistics costs but also a key mechanism for improving smallholder farmers’ income and service levels. This study provides a unified analytical framework for integrating routing optimization and profit allocation, offering valuable insights for collaborative logistics decision-making, alliance cost-sharing mechanisms, and related operations research problems. Furthermore, the results indicate that the effectiveness of collaborative transportation is closely related to the organizational structure on the supply side and the spatial distribution on the demand side, suggesting that coordination mechanisms play an important role in improving overall system efficiency in decentralized agricultural systems.

Key words: logistics collaboration, Shapley allocation, contract farming, farmers' income