Abstract:  In order to minimize the total unproductive operation time and waiting time of unproductive operation, a multimachine and multitask collaborative optimization scheduling model was constructed in this paper to solve the problems such as unreasonable operation path planning of combine harvester and inability of coordinated optimization scheduling between combine harvester and grain truck, and a multiMachine Cooperative Optimal Scheduling algorithm (MMCOSA) was designed. Firstly, the static path planning scheme of the combine harvester was calculated by improving the traditional ACO algorithm. Then, the relative distance nearest strategy was adopted to realize the dynamic optimization of cooperative operation between combine harvester and grain truck. The experimental results showed that the total nonproductive operation time and nonproductive operation waiting time calculated by MMCOSA algorithm in this paper were both 17.5% and 19.02% shorter than the results of traditional ACO algorithm. MMCOSA algorithm not only accelerated the convergence rate, but also shorted the operation time, which could provide an effective solution to the cooperative scheduling problem of combine harvester and grain truck in busy farming season.

Key words: combine harvester, grain truck, collaborative operation, ant colony algorithm, path planning, scheduling

摘要： 针对联合收割机作业路径规划不合理、联合收割机与运粮车无法协同优化调度等问题，以最小化联合收割机总非生产性作业时间和非生产性作业等待时间为目标，构建多机型多任务协同优化调度模型，设计多机协同优化调度算法(MMCOSA)。首先通过对传统蚁群算法(ACO)进行改进，计算得到联合收割机的静态路径规划方案，然后采用相对距离最近策略实现联合收割机与运粮车协同作业动态优化。试验结果表明，采用MMCOSA算法计算得到的联合收割机总非产性作业时间和非生产性作业等待时间均比传统ACO算法的结果平均缩短17.5%和19.02%，MMCOSA算法不仅加快收敛速度，而且缩短作业时间，为农忙时节联合收割机与运粮车的协同调度问题提供有效的解决方案。

关键词: 联合收割机, 运粮车, 协同作业, 蚁群算法, 路径规划, 调度