基于谐振子遗传算法的高效地下水优化管理模型
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  • 英文篇名:New Harmonic Oscillator Genetic Algorithm for Efficient Groundwater Optimization and Management
  • 作者:吴鸣 ; 吴剑锋 ; 施小清 ; 刘杰 ; 陈干 ; 吴吉春
  • 英文作者:Wu Ming;Wu Jianfeng;Shi Xiaoqing;Liu Jie;Chen Gan;Wu Jichun;Department of Hydrosciences,School of Earth Sciences and Engineering,Nanjing University;Center for Water Research,College of Engineering,Peking University;
  • 关键词:谐振子遗传算法 ; 遗传算法 ; 模拟谐振子算法 ; 地下水管理模型 ; 全局搜索能力 ; 寻优效率 ; 华北平原
  • 英文关键词:harmonic oscillator genetic algorithm;;genetic algorithm;;simulated harmonic oscillator algorithm;;groundwater management model;;global searching ability;;optimization efficiency;;North China Plain(NCP)
  • 中文刊名:CCDZ
  • 英文刊名:Journal of Jilin University(Earth Science Edition)
  • 机构:南京大学地球科学与工程学院水科学系;北京大学工学院水资源研究中心;
  • 出版日期:2015-09-26
  • 出版单位:吉林大学学报(地球科学版)
  • 年:2015
  • 期:v.45
  • 基金:国家自然科学基金资助项目(41372235,41072175);; 国家“973”计划项目(2010CB428803)
  • 语种:中文;
  • 页:CCDZ201505020
  • 页数:8
  • CN:05
  • ISSN:22-1343/P
  • 分类号:220-227
摘要
在传统遗传算法和模拟谐振子算法的基础上,结合两者的优点,提出了一种新型快速高效的谐振子遗传算法。通过一个理想的水资源管理模型的算例和一个华北平原典型区地下水资源优化的实际算例,从寻优结果和寻优效率两个方面对谐振子遗传算法、传统遗传算法和模拟谐振子算法进行了对比分析。在两个地下水管理模型中,与传统的遗传算法和模拟谐振子算法相比,新型的谐振子遗传算法搜索效率达到模拟谐振子算法搜索效率的2倍以上,得到的最优解比遗传算法所得到的最优解分别增加供水量1.1×103 m3/d和0.47×108 m3/a,说明谐振子遗传算法具有更强的全局搜索能力和更好的寻优效率。
        Combining the advantages of conventional genetic algorithm(GA)with simulated harmonic oscillator algorithm(SHOA),we put forward a new efficient harmonic oscillator genetic algorithm(HOGA).Based on the application to an ideal test and an optimization test for the groundwater management model of a typical region in North China Plain(NCP),the comparisons among GA,SHOA and HOGA are performed in respect both of the quality of optimal solutions and the efficiency of algorithmic optimization.Compared with GA and SHOA,HOGA achieves an efficiency over two times higher than SHOA.The best pumping schemes achieved by HOGA can increase water supply by 1.1×103 m3/d and 0.47×108 m3/a compared with the pumping schemes achieved by GA in the two groundwater management models.This reveals that HOGA has the best global searching abilitywith the highest optimization efficiency.The results suggest that the HOGA presented in this study be of extensive perspectives in application to multi-dimensional and nonlinear groundwater management and optimization.
引文
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