摘要
为了解决地面沉降区地下水资源科学管理这一个重要的资源与环境地质问题,基于模拟优化(S-O)模型的思想,建立了考虑地面沉降约束的地下水模拟优化管理模型(SUBGO).模拟模型采用地下水模拟程序MODFLOW-2005中的地面沉降模拟子程序SUB-WT来模拟地面沉降过程.优化模型分别采用遗传算法(GA)和小生境Pareto禁忌遗传混合算法(NPTSGA)分别求解单目标和多目标的优化设计方案.将SUBGO管理模型应用于一个理想场地含水层中地下水开采方案和地面沉降控制的优化设计中,结果表明基于GA的单目标优化和基于NPTSGA的多目标优化均能搜索到全局最优解和全局分布的Pareto最优解,均能够在控制地面沉降的约束条件下,设计合理的地下水开采利用方案.与单目标相比,多目标优化能够为决策者提供多个解作为管理决策方案,同时多目标优化还提高了寻优的计算效率.
A linked simulation-optimization（S-O）model（SUBGO）is developed for deriving multiple objective management strategies for rational utilization of groundwater resources and disaster mitigation considering constraints of land subsidence.The SUB-WT,which is the compaction package of MODFLOW2005,is used to generate input-output patterns of groundwater extraction rates and vertical compaction.The genetic algorithm（GA）and the niched Pareto tabu search combined with a genetic algorithm（NPTSGA）are incorporated with SUB-WT model to find global optimal solution for single objective optimization problem and to generate Pareto-optimal solutions set for multi-objective optimization problem.The performance of the presented simulation-optimization model is evaluated throughasynthetic example application.The optimization results indicate that both the GA-based single objective optimization and NPTSGA-based multi-objective optimization can obtain the optimal groundwater pumping schemes under different constraints.Compared with single objective optimization,multi-objective optimization can provide multiple Pareto-optimal solutions for decision-making and the computational efficiency is greatly improved.
出处
《南京大学学报（自然科学版）》
CAS
CSCD
北大核心
2016年第3期470-478,共9页
Journal of Nanjing University（Natural Science）
基金
国家自然科学基金(41402198)
江苏省基础研究计划(自然科学基金)--青年基金(BK20131009)
关键词
地面沉降
地下水管理
模拟优化
遗传算法
混合多目标进化算法
land subsidence
groundwater management
simulation-optimization
genetic algorithm
hybrid multi-objective evolutionary algorithm
