基于多作物总产量最大的灌溉优化模型与算法研究  

Irrigation Optimization Model and Algorithm Based on Maximum Total Gains of Multiple Crops

作　　者：杨习清[1] 柴强 谢军红[3] 

机构地区：[1]甘肃农业大学理学院,兰州730070 [2]甘肃省干旱生境作物重点实验室,兰州730070 [3]甘肃农业大学农学院,兰州730070

出　　处：《中国农村水利水电》2015年第5期11-13,22,共4页China Rural Water and Hydropower

基　　金：国家公益性行业项目(201103001);973前期研究专项(2012CB722902);甘肃农业大学盛彤笙科技创新基金项目(GSAU-STS-1240)

摘　　要：我国北方地区灌溉水资源极度缺乏,如何将有限的灌溉水资源有效分配到多种作物间是一个重要问题。为此,在考虑作物敏感系数、有效降雨量、土壤含水量等因素的同时,还考虑了作物的市场价格和单位产量因素,建立了多作物、多约束的非线性灌溉优化模型。引入粒子群算法(PSO)时,借鉴遗传算法中杂交的概念,得到了基于杂交的混合粒子群算法(BreedPSO),并应用实例进行计算,求解结果表明该模型能很好解决多作物间灌溉水量优化配置问题,同时也验证了该算法的有效性和可行性。Irrigation water shortage in North China is very serious,so how to allocate the limited water effectively among various crops is an important issue.Therefore,in considering the sensitive crop coefficients,effective rainfall,soil moisture,market price,unit output and other factors,this paper establishes a multi-crop,multi-constrained nonlinear optimization model of irrigation.When introducing particle swarm optimization（PSO）,learning the concept of hybridization in genetic algorithm,this paper gets a hybrid particle swarm algorithm is based on hybridization（Breed PSO）.The results of one example show that the model can solve the multiple crops irrigation allocation problem,and demonstrate the effectiveness and feasibility of the hybrid particle swarm algorithm.

关 键 词：多作物 灌溉优化 粒子群算法 杂交 

分 类 号：S275[农业科学—农业水土工程]