基于IABC-PSO算法的区域水资源优化配置模型研究  

Research on optimal allocation model of regional water resources based on IABC-PSO algorithm

作　　者：冀宁远 杨侃[1] 陈静 杨晶晶 JI Ningyuan;YANG Kan;CHEN Jing;YANG Jingjing(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China;Yixing Water Resources Bureau,Wuxi 214207,China)

机构地区：[1]河海大学水文水资源学院,江苏南京210098 [2]宜兴水利局,江苏无锡214207

出　　处：《人民长江》2021年第6期49-57,87,共10页Yangtze River

基　　金：山西省水利科学技术研究与推广项目“复杂大水网水库群联合优化调度关键技术研究”(2017DSW02);云南省水利厅科技项目“水资源综合节水与非常规水源利用研究”;国家重点基础研究发展计划(973计划)项目(2012CB417006)。

摘　　要：近年来山西省水资源供需矛盾日益突出,采用科学有效的方法对该区域水资源进行优化配置十分关键。在综合考虑社会、经济、生态效益的基础上,建立了多目标水资源优化配置模型。针对传统粒子群算法的缺点,提出了改进的人工蜂群-粒子群算法(IABC-PSO);通过引入Logistic混沌映射、基于S型函数的非线性惯性权重以及改进的侦查蜂搜索算子,提升了算法的收敛精度及全局寻优能力。以晋中南部供水区为实例,运用IABC-PSO算法进行了水资源调配计算及分析。研究成果可为山西省“大水网”建设背景下的区域水资源配置提供一种新的求解思路。In recent years,the contradiction between supply and demand of water resources in Shanxi Province has become increasingly prominent.So it′s very crucial to optimize the allocation of regional water resources through scientific and effective methods.In this paper,we established a multi-objective optimal allocation model of water resources based on the comprehensive consideration of social,economic and ecological benefits.Aiming at the shortcomings of traditional Particle Swarm Optimization(PSO)algorithm,we proposed an Improved Artificial Bee Colony-Particle Swarm Optimization(IABC-PSO)algorithm.By using Logistic chaotic map,nonlinear inertial weight based on S-type function and improved scout bee search operator,the convergence accuracy and global optimization ability of the algorithm were enhanced.On this basis,we allocated and calculated water resources of water supply district in south of Central Shanxi Province by using IABC-PSO algorithm.This paper can provide a new idea for the optimal allocation of water resources under the background of the construction of Shanxi water network.

关 键 词：区域水资源优化配置 多目标优化模型 改进的人工蜂群-粒子算法 混沌变量 晋中南部供水区 

分 类 号：TV213.9[水利工程—水文学及水资源]