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

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