| 双种群进化粒子群算法求解地下水管理模型 |
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| 引用本文： | 吴睿奇,朱国荣,王 佩.双种群进化粒子群算法求解地下水管理模型[J].地质学刊,2012,36(1):37-43. |
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| 作者姓名： | 吴睿奇 朱国荣 王 佩 |
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| 作者单位： | 南京大学地球科学与工程学院 |
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| 基金项目： | 国家自然科学基金项目（J0830522）资助 |
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| 摘 要： | 为避免粒子群算法(PSO)早熟的缺点，设计了一种双种群进化粒子群算法(DE-PSO)。DE-PSO是基于PSO，引入选择、交叉及差分变异操作，并结合合理有效的粒子评价方法及越界处理方法之后形成的。将DE-PSO应用于两个地下水管理模型算例，第一个算例DE-PSO解的总抽水量分别比遗传算法(GA)、模拟退火算法(SA)和PSO减少了64、256、207 m3/d，第二个算例DE-PSO解的总治理成本分别比GA、SA和PSO减少了57.74、151.93、76.59万元。两个算例中DE-PSO都表现出稳定的进化趋势，寻优效率好于GA、SA和PSO，可以有效求解地下水管理模型问题。
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| 关 键 词： | 地下水管理模型 粒子群算法 双种群 差分变异 |
| 收稿时间： | 2011/10/26 0:00:00 |
Double-population evolution-particle swarm optimization algorithm for solving groundwater management model |
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| WU Rui-qi.Double-population evolution-particle swarm optimization algorithm for solving groundwater management model[J].Jiangsu Geology,2012,36(1):37-43. |
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| Authors: | WU Rui-qi |
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| Institution: | (School of Earth Sciences and Engineering,Nanjing University,Nanjing 210093,China) |
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| Abstract: | To solve the premature convergence problem of Particle Swarm Optimization(PSO),a new algorithm named DE-PSO(Double-population Evolution-Particle Swarm Optimization) was designed.DE-PSO introduced selection,crossover and differential mutation into PSO,and adopted a new evaluation method to evaluate swarms and a new control method to ensure all swarms can fly inside search space.DE-PSO was applied to solve two groundwater management cases.In the first case,DE-PSO produced a design with respectively 64,256 and 207 m3/d less pumping rate than those of GA 、SA and PSO;in the second case,DE-PSO produced a design with respectively $577,400,$1,519,300 and $765,900 less remedial design cost than those of GA,SA and PSO.Two case studies indicated that DE-PSO could evolve steadily,the searching efficiency was better than GA,SA and PSO.DE-PSO could solve groundwater management model problems effectively. |
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| Keywords: | Groundwater management model Particle swarm optimization Double population Differential variation |
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