摘要
由于缺少科学合理的优化调度策略,在农收季节多机跨区作业常常出现作业成本高、作业效率低、无法在适宜作业的时间内完成农田任务等情况。针对此问题,在作业时间窗的约束下,以农机作业转移距离最短、调度总成本最低为目标,构建多机多目标跨区协同作业调度模型,设计基于优先级策略的多目标自适应优化调度算法(APRMOGA)。采用双层编码方式对基因进行编码,按照时间窗优先级规则依次分配联合收割机进行作业,产生初始种群;设计基于双层编码的时间窗优先级顺序交叉方法,优先保留开始作业时间早的基因,结合自适应变异概率和精英策略对个体进行选择变换,得到全局最优的Pareto解集。选取河北省内某地区24块农田进行试验验证,结果表明:APRMOGA算法运行效率要高于NSGA-Ⅱ算法;通过APRMOGA算法计算得到的联合收割机作业转移距离和调度总成本比NSGA-Ⅱ算法分别下降23.60%、13.72%。
Due to the lack of scientific and reasonable optimization and scheduling strategies,multi‑machine cross‑regional operations during the agricultural harvest season often result in high operational costs,low operation efficiency and the inability to complete field tasks within the optimal time frame.In order to address this issue,a multi‑machine and multi‑objective cross‑regional collaborative operation scheduling model was constructed,targeting the shortest transfer distance for agricultural machinery and the lowest total scheduling cost under the constraint of operation time windows.A multi‑objective adaptive priority‑based optimization scheduling algorithm(APRMOGA)was designed.The genes were encoded by dual‑layer encoding method,the combine harvesters were assigned successively for operation according to time window priority rules to generate the initial population.A time window priority sequence crossover method based on dual‑layer encoding was designed to preferentially retain genes with earlier start times.This is combined with adaptive mutation probability and elitism strategies to select and transform individuals,and obtain the globally optimal Pareto solution set.An experiment was conducted by using 24 fields in a certain region of Hebei Province for verification.The results indicated that the operational efficiency of the APRMOGA algorithm was higher than that of the NSGA-II algorithm.The transfer distance and total scheduling cost of combine harvesters calculated by the APRMOGA algorithm were reduced by 23.60%and 13.72%,respectively,compared to the NSGA-II algorithm.
作者
郭亚倩
张璠
姚竟发
常淑惠
孟宇
于春辉
Guo Yaqian;Zhang Fan;Yao Jingfa;Chang Shuhui;Meng Yu;Yu Chunhui(College of Information Science and Technology,Hebei Agricultural University,Baoding,071000,China;Key Laboratory of Agricultural Big Data of Hebei Province,Baoding,071000,China;Software Engineering Department,Hebei Software Institute,Baoding,071000,China;College of Continuing Education,Hebei Agricultural University,Baoding,071000,China)
出处
《中国农机化学报》
北大核心
2024年第10期184-192,共9页
Journal of Chinese Agricultural Mechanization
基金
河北省重点研发项目(21327407D)
河北省高等学校科学研究项目(QN2023062)
河北省自然科学基金项目(C2023204069)。
关键词
农机
时间窗优先级策略
多目标优化
路径规划
agricultural machinery
time window prioritization strategy
multi‑objective optimization
path planning
