摘要
针对多区域互联农机服务资源分配不合理所导致的区域整体经济效益低下的问题,采用数学建模与智能优化算法相结合的仿真方法,对多区互联农机服务资源配置进行研究。结合智慧农业发展现状和多区域互联农机服务调度特点,构建多区域协调调度架构,获取全局农机服务资源状况;建立价值可变的多背包农机服务调度模型,设计改进模拟退火和粒子群优化的混合智能算法求解调度模型;通过实例分析本研究设计的协调调度方法与传统分散调度方法的区域总效益、订单响应率和农机效用比的差异性以及农田面积对调度方法的影响。仿真结果表明,当订单数量<375时,2种调度方法所产生的效果相同;当订单数量≥375时,协调调度方法所得农机效用比高于传统分散调度方法2.74%,当订单数量≥625时,协调调度方法所得区域总效益和订单响应率比传统分散调度方法分别高10.65%和14.88%。
Aiming at the problem of low overall regional economic benefit caused by unreasonable allocation of agricultural machinery service resources in multi-region interconnection,a simulation method combining mathematical modeling and intelligent optimization algorithm were used to study the allocation of agricultural machinery service resources in multi-region interconnection.According to the development status of intelligent agriculture and the characteristics of multi-regional interconnected agricultural machinery service scheduling,a multi-regional coordination scheduling architecture was constructed to obtain the overall situation of agricultural machinery service resources.A multi-knapsack agricultural machinery service scheduling model with variable value was established,and a hybrid intelligent algorithm based on simulated annealing and particle swarm optimization was designed to solve the scheduling model.An example was given to analyze the difference between the coordinated dispatching method and the traditional decentralized dispatching method in terms of regional total benefit,order response rate and agricultural machinery utility ratio,and the influence of farmland area on the dispatching method.The simulation results showed that when the number of orders was less than 375,the effect of the two scheduling methods was the same;When the number of orders was more than 375,the utility ratio of agricultural machinery obtained by the coordinated scheduling method was2.74%higher than that of the traditional decentralized scheduling method;When the number of orders was more than625,the total regional benefit and order response rate of the coordinated scheduling method were respectively 10.65%and 14.88%higher than those of the traditional decentralized scheduling method.
作者
马军岩
袁逸萍
任年鲁
郭宇
刘湘
MA Junyan;YUAN Yiping;REN Nianlu;GUO Yu;LIU Xiang(College of Mechanical Engineering,Xinjiang University,Urumqi 830049,China;College of Mechanical and Electrical Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《中国农业大学学报》
CAS
CSCD
北大核心
2020年第4期113-122,共10页
Journal of China Agricultural University
基金
科技援疆项目(2019E0213)。
关键词
智慧农业
协调调度
模拟退火和粒子群优化混合算法
资源优化配置
intelligent agriculture
coordinated scheduling
hybrid algorithm of simulated annealing and particle swarm optimization
optimal allocation of resources
