地质论评Issue(3)：570-578,9.DOI:10.16509/j.georeview.2015.03.010
参数空间变异性下地下水污染监测网多目标优化机制研究
The Study on Multi-objective Optimization for Groundwater Monitoring Network Design under Spatial Variation of Parameters
摘要
Abstract
Based on the fact that there is spatial variation of hydraulic conductivity,a new probabilistic Pareto genetic algorithm (PPGA ) is developed to solve multi-objective optimal design of groundwater contaminant monitoring network under the spatial variation of hydraulic conductivity.The PPGA is developed by adding the probabilistic Pareto domination ranking and probabilistic niche technique to the classic epsilon-dominance non-dominated sorted genetic algorithm II (ε-NSGAII ) to search for Pareto optimal solutions of multi-objective optimization problems under uncertainty.The Pareto optimal solutions are then compared with the MC analysis results to demonstrate the effectiveness and reliability of the PPGA.Comprehensive analysis demonstrates that the proposed PPGA can find Pareto-optimal solutions with low variability and high reliability and can provide a range of reliable monitoring programs for decision makers under the spatial variation of hydraulic conductivity.关键词
地下水污染/监测网设计/随机多目标优化/遗传算法Key words
groundwater contamination/monitoring network design/probabilistic multi-objective optimization/genetic algorithm引用本文复制引用
骆乾坤,吴剑锋,杨运,钱家忠..参数空间变异性下地下水污染监测网多目标优化机制研究[J].地质论评,2015,(3):570-578,9.基金项目
本文为中央高校基本科研业务费专项资金资助项目（编号 J2014HGBZ0186，J2014HGBZ0119）、国家自然科学基金资助项目（编号41072175，41372235，41272251，41372245）的成果。 （）
