Unmanned aerial vehicles (UAVs) are increasingly used in instant delivery scenarios. The combined delivery of vehicles and UAVs has many advantages compared to their respective separate delivery, which can greatly improve delivery efficiency. Although a few studies in the literature have explored the issue of vehicle-assisted UAV delivery, we did not find any studies on the scenario of an UAV serving several customers. This study aims to design a new vehicle-assisted UAV delivery solution that allows UAVs to serve multiple customers in a single take-off and takes energy consumption into account. A multi-UAV task allocation model and a vehicle path planning model were established to determine the task allocation of the UAVs as well as the path of UAVs and the vehicle, respectively. The model also considered the impact of changing the payload of the UAV on energy consumption, bringing the results closer to reality. Finally, a hybrid heuristic algorithm based on an improved K-means algorithm and ant colony optimization (ACO) was proposed to solve the problem, and the effectiveness of the scheme was proven by multi-scale experimental instances and comparative experiments.

The traditional performance evaluation method, which is mainly based on financial indexes, is no longer applicable to the current dynamic, complex, and coordinated evaluation of the service quality of fresh agricultural produce supply chains. Comprehensive evaluations regarding the quality of coordination-based supply chain services are now required. Specific analyses of index weights, the identification of potential problems, the exploration of the best solutions, and efforts to improve the current situation—regarding the circulation of fresh agricultural products—are also required. By carrying out this research, this paper aims to construct a coordination-based service quality evaluation index system for the fresh agricultural produce supply chain platform. The evaluation system that was created covered the four dimensions involved in platform supply chain coordination. These dimensions are capital flow, logistics, business flow, and information flow. On this basis, this study designed a survey questionnaire to collect data to evaluate customer service quality satisfaction. The research used AHP and the Fuzzy Comprehensive Evaluation method to calculate and analyze indexes and models in the “Fresh Networking” project. Furthermore, this paper proposed a sensitivity analysis model of MCDM evaluation indexes and their weights. In order to verify whether the numerical analysis method was suitable for use in the MCDM evaluation system, in this paper, the sensitivity analysis process of the indexes and their weights was introduced in the evaluation of the “Fresh Networking” project. The evaluation results may reflect the real quality of service in the “Fresh Network” supply chain. The final conclusion to be drawn from this paper is that capital flow is the most sensitive weight, which means that it should be designed and implemented in accordance with optimization-based decisions. The novelty of this paper lies in: (1) the proposal of a coordination-based service quality evaluation index system which includes four dimensions: capital flow, logistics, business flow, and information flow; (2) the design of a research questionnaire for data collection; and (3) the introduction of an improved sensitivity analysis method for the MCDM index. The results presented in this paper will enrich the theoretical research related to MCDM in supply chain evaluations. The results of the analysis can be used to guide supply chain decision makers to make optimization decisions accordingly, which will ensure overall benefits in terms of supply chain coordination, improving the capacity of preservation services, and loss reduction.

With changes in demand and the emergence of new distribution channels, consumer-centric buyer’s markets for many products have been formed. The platform supply chain has been continuously optimized and upgraded. Supply chain leaders have moved downstream to the end of the supply chain. The operational value has been further enhanced. The corresponding systematic construction of the platform supply chain has become an important driving force for future development. The model in this paper is different from the traditional supply chain contract model, which mainly focuses on suppliers or demand. In order to meet the requirements of fresh-keeping services and the goal of revenue sharing, we integrate the production and circulation characteristics of fresh produce into the design of a contract model. In this paper, a revenue-sharing contract model of the fresh produce supply chain is constructed based on the core position of retailers, the uncertainty of the market size, and the consideration of a fresh-keeping service. The model is mainly composed of the core retailer and the supplier. Through further numerical analysis, we verify the effectiveness of the revenue-sharing contract model in supply chain coordination. We also analyze the change trends in the optimal retail price, optimal freshness level, and optimal order quantity caused by changes in both the fresh-keeping service capacity and the revenue-sharing coefficient. The results show that after changing these two parameters, the supply chain can achieve coordination under the specified parameter values. The changed parameters will also lead to certain change trends in the optimal retail price, optimal freshness level, and optimal order quantity, and will have a corresponding impact on the stability of supply chain operation. This research provides a relevant theoretical and empirical basis for a fresh produce supply chain contract model with retailers at the core position. We also provide guidance and reference for optimizing the supply chain management mode and improving the overall operational efficiency of the fresh produce supply chain.