Abstract
This study proposes a groundwater management model in which the solution is performed through a combined simulation-optimization model. In the proposed model, a modular three-dimensional finite difference groundwater flow model, MODFLOW is used as simulation model. This model is then integrated with an optimization model, in which a modified Pareto dominance based Real-Coded Genetic Algorithm (mPRCGA) is adopted. The performance of the proposed mPRCGA based management model is tested on a hypothetical numerical example. The results indicate that the proposed mPRCGA based management model is an effective way to obtain good optimum management strategy and may be used to solve other type of groundwater simulation-optimization problems.
Highlights
Groundwater is a vital resource throughout the world
The remaining of this paper is organized as follows: firstly, the formulation of groundwater management model is described; secondly, a modified Pareto based Real-Coded Genetic Algorithm with generalized generation gap model and a modified SPX operator is proposed; thirdly, performance of the proposed modified Pareto dominance based RealCoded Genetic Algorithm (mPRCGA) based management model is tested on a hypothetical example
The results obtained by mPRCGA satisfies the requirement of symmetry of aquifer system, this verify the reliability of MPRCGA
Summary
Groundwater is a vital resource throughout the world. Nowadays, with increasing population and living standards, there is a growing need for the utilization of groundwater resources. Relevant methods proposed for constraint handling for heuristic optimization approaches can be categorized into: 1) penalty function methods; 2) methods based on preserving feasibility of solutions; 3) methods which make a clear distinction between feasible and infeasible solutions; and 4) hybrid methods [17] [23] [24]. Among these constraint handling techniques, methods based on multi-objective concepts have attracted increasing attention. The remaining of this paper is organized as follows: firstly, the formulation of groundwater management model (simulation model and optimization model) is described; secondly, a modified Pareto based Real-Coded Genetic Algorithm (mPRCGA) with generalized generation gap model and a modified SPX operator is proposed; thirdly, performance of the proposed mPRCGA based management model is tested on a hypothetical example
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