摘要
为了解决灌区水资源配置中的信息采集方法落后和多目标模型求解易陷入局部最优等问题,通过伪随机并行搜索和最近邻域选择等策略对Pareto蚁群算法进行改进,然后将Pareto蚁群算法与3S技术耦合,以宁夏银北灌区为仿真对象,利用改进的Pareto蚁群算法计算灌区多目标、多约束的水资源空间优化配置模型,获得最优的井灌水量、渠灌水量、排水量以及最优的经济效益和灌排费用。基于Pareto蚁群算法和3S技术的灌区水资源空间优化配置,能加快算法的收敛速度,获得全局最优解,使优化结果更接近实际,对灌区的水资源宏观调度具有一定的参考价值。
To allocate water resources in irrigated areas by using a multi-objective model, some problems must be solved, for exam- ple, information acquisition problem and falling into local optimuln. A Pareto ant colony algorithm （PACA） is introduced and im proved through two strategies： pseudo random parallel search and nearest neighbor selection. Then PACA is coupled with 3S （GIS, RS and GPS） technology. Yinbei Irrigation District in Ningxia is selected as a case study. Optimal spatial allocation model of water resources in irrigated areas, with multi-objective, multi-constraint and pixel-based characteristics, is calculated in the PACA-based GIS platform. Finally, allocation schemes, including irrigation water from wells and canals, drainage volume, economic benefit and costs from irrigation and drainage, are optimized. The integration of PACA with 3S technology can accelerate the PACA conver- gence, and simultaneously obtain the global optimal solution. Therefore, the method makes the optimization results closer to the re ality for support and decision of water resource scheduling in irrigated areas.
出处
《中国农村水利水电》
北大核心
2014年第3期166-168,171,共4页
China Rural Water and Hydropower
基金
宁夏大学自然科学基金重点项目(ZR1209)
关键词
Pareto蚁群算法
3S技术
灌区
水资源
优化配置
Pareto ant colony algorithm （PACA）
3S technology
irrigated area
water resources~ optimal allocation
