Supply Chain Scheduling Optimization in an Agricultural Socialized Service Platform Based on the Coordination Degree

Abstract

In order to create a sustainable agricultural production system and meet the multi-stage and differentiated production needs of farmers, this study proposes to build an agricultural service platform to dispatch agricultural service providers. Reasonably handling the collaborative relationship between farmers and service providers is a key issue in platform scheduling. Based on the analysis of the operation characteristics of the agricultural service platform, this study redefines the core issue of handling the collaborative relationship—the coordination degree—from the special characteristics of agricultural services, then analyzes it in depth and proposes a portrayal method. On this basis, a multi-stage and multi-objective scheduling optimization model, which integrally reflects the service utility and service combination operation efficiency, is constructed, and an improved genetic algorithm is proposed for solving it. Then, this study designs a numerical experiment which describes the multi-stage decision making of farmers, and the simulation results show that the optimization model can provide a balanced multi-objective supplier scheduling solution for them. Further, the validity and feasibility of the model and algorithm are verified through comparative tests of optimization effects and sensitive analysis. This study contributes to research on sustainable agriculture by modeling collaboration between smallholder farmers and agricultural service providers, and provides an effective decision-making tool for agricultural service platforms.