Authors

Abstract

To address problems involving the poor matching ability of supply and demand information and outdated scheduling methods in agricultural machinery operation service, in this study, we proposed a harvester operation scheduling model and algorithm for an order-oriented multi-machine collaborative operation within a region. First, we analysed the order-oriented multi-machine collaborative operation within the region and the characteristics of agricultural machinery operation scheduling, examined the revenue of a mechanized harvesting operation and the components of each cost, and constructed a harvester operation scheduling model with the operation income as the optimization goal. Second, we proposed a simulated annealing genetic algorithm-based harvester operation scheduling algorithm and analysed the validity and stability of the algorithm through experimental simulations. The results showed that the proposed harvester operation scheduling model effectively integrated the operating cost, transfer cost, waiting time cost, and operation delay cost of the harvester, and the accuracy of the harvester operation scheduling model was improved; the harvester operation scheduling algorithm based on simulated annealing genetic algorithm (SAGA) was able to obtain a global near-optimal solution of high quality and stability with high computational efficiency.

Abstract in Chinese

针对农机作业服务供需信息匹配能力弱、调度方式落后的问题，该文针对区域内面向订单的多农机协同作业模式，建立了收割机调度模型及算法。首先对区域内面向订单的多农机协同作业模式进行了明确，并建立了以机收作业总收益为优化目标的收割机作业调度模型；其次，设计了基于模拟退火遗传算法的收割机作业调度算法，并通过相关仿真实验对算法的有效性、稳定性及计算效率进行了分析。研究结果表明：建立的收割机作业调度模型有效整合了使用成本、转移成本、等待时间成本、延误作业损失成本信息，提高了收割机作业调度模型的准确性；基于模拟退火遗传算法的收割机作业调度算法可以获得质量较高的全局近优解，具有较高的计算效率。