基于蚁群算法的农业节水灌溉路径优化部署  

Study on Pheromone-based Ant Colony Algorithm For Optimal Proliferation

作　　者：邓蕾蕾[1] 于合龙[1] 于亚洲[2] 张献[3] 

机构地区：[1]吉林农业大学信息技术学院,长春130118 [2]大连理工大学软件学院,大连116024 [3]长春大学教务处,长春130022

出　　处：《吉林农业大学学报》2012年第2期221-224,229,共5页Journal of Jilin Agricultural University

基　　金：吉林省科技厅青年科研基金研究项目(201000153)

摘　　要：为实现节水灌溉田间地块路径管线部署的管理和控制,采用信息素优化的改进蚁群算法进行设计研究。在现有蚁群算法组合优化的现实缺陷基础上,以田间地块坐标作为数据源,采用改进的蚁群算法对田间地块布线路径进行设计,从而提高蚁群算法在迭代过程中更新最优解的能力,最终在相同的迭代次数内找到路径更短、代价更小的规则,解决农业节水灌溉管线路径部署优化问题,并在VC++程序中验证路径优化的实际问题。测试结果表明:在相同的气候条件下,路径优化部署设计结果可以为节水灌溉的管道布局管理提供参考依据和数据支持。In order to realize the water-saving irrigation of field plots path pipeline deployment management and control,ant colony algorithm with optimized pheromone was designed.Based on the defects of the existing ant colony algorithm combinatorial optimization,with the coordinate of field plots as data source,an improved ant colony algorithm for field plots wiring path was designed to improve the ability to update the optimal solution of ant colony algorithm in an iterative process and finally in the same number of iterations to find the rules of a shorter path and of less cost,to solve the problem of agricultural water-saving irrigation pipeline path optimization and to verify the actual problems in the VC＋＋program validation path optimization.The test results show that,under the same climatic conditions,path optimization design results can provide reference basis and data support for water saving irrigation pipeline layout management.

关 键 词：信息素 信息素扩散 蚁群算法 节水灌溉 

分 类 号：S274[农业科学—农业水土工程] TP39[农业科学—农业工程]