遗传算法在蔬菜移栽机参数优化中的应用  

Application of genetic algorithm on the parameters optimization of vegetable seedling transplanter

作　　者：王笑岩[1] 王石[2] 

机构地区：[1]朝阳师范高等专科学校数学计算机系,辽宁朝阳122000 [2]沈阳工程学院机械学院,沈阳市110136

出　　处：《中国农机化学报》2015年第1期139-141,148,共4页Journal of Chinese Agricultural Mechanization

基　　金：辽宁省高教学会"十二五"高等教育科研课题(GHYB110216)

摘　　要：以挠性圆盘蔬菜移栽机为研究对象,建立秧苗落地角度优化模型,将零速投苗原理转化为约束条件应用于优化模型中,根据优化模型实际情况选择适应度函数及个体适应度值计算选择方法。针对遗传算法收敛速度、规定的迭代次数内进化不完全和易落入局部最优解等缺陷,引入了一种改进遗传操作方法。对秧苗落地角度最佳的寻优计算后得到投苗过程中影响秧苗落地角度的移栽机投苗机构参数、运动参数及栽植参数。根据优化结果与实际生产情况和农艺要求相结合选择的参数进行秧苗移栽试验,试验结果表明遗传算法适用本文优化问题。研究结果为蔬菜移栽机的机构参数化设计、优化设计和试验研究提供了理论依据。Using soft disc vegetable seedling transplanter as the object, an optimization model for landing angle was built and constraint conditions converted from zero-speed seedling principle were applied in it. The fitness function and individual fitness value calculation method were selected according to the actual condition of the model. Aiming at the drawbacks that genetic algorithm has low convergence rate, usually shows incomplete evolution within the specified iterations and could easily get trapped in local optima, an improved genetic algorithm （IGA） was proposed. After the optimization calculation for landing angle, the seedling mechanism parameters, kinematics parameters and planting parameters that could affect the landing angle were acquired. A seedling transplanting experiment was conducted with the parameters selected according to the optimization results and the actual production as well as agronomic requirements. The improved genetic algorithm is applicable to the optimization problem in this paper. The research results can provide a theoretical basis for mechanism parameter design, optimization design and experimental study of vegetable transplanter.

关 键 词：改进遗传算法 蔬菜移栽机 挠性圆盘 参数优化 落地角度 

分 类 号：S223.94[农业科学—农业机械化工程]