A Hybrid Multi‐Objective Evolutionary Algorithm for Optimal Groundwater Management under Variable Density Conditions
A Hybrid Multi‐Objective Evolutionary Algorithm for Optimal Groundwater Management under Variable Density Conditions
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DOI：
10.1111/j.1755-6724.2012.00625.x
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发表时间：
2012-02
期刊：
影响因子：
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通讯作者：
Y. Yun;Jianfeng Wu;Xiaomin Sun;Lin Jin;Jichun Wu
中科院分区：
文献类型：
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作者：
Y. Yun;Jianfeng Wu;Xiaomin Sun;Lin Jin;Jichun Wu
针对变密度条件下地下水资源管理问题，提出了一种新的混合多目标进化算法(MOEA)--小生境Pareto Tabu搜索与遗传算法(NPTSGA)相结合。相对较少的MOEA能够具有全局搜索能力，以满足局部区域的强化搜索。此外，基于禁忌搜索的多目标进化算法的全局搜索能力对邻域步长非常敏感。NPTSGA是基于将遗传算法(GA)与基于TS的MOEA--小生境Pareto Tabu Search(NPTS)相结合的思想发展起来的，它有助于缓解上述两个困难。通过进化遗传算法种群产生的候选解的多样性，提高了NPTS的全局搜索能力。此外，本文还开发了一个与密度相关的地下水流动和溶质运移模拟器SEAWAT，并通过一个综合海水入侵管理问题对其性能进行了评估。优化结果表明，NPTSGA在两个相互冲突的目标之间提供了折衷。本研究的一个关键结论是，NPTSGA在非支配的强化和近帕累托最优解沿折衷曲线的多样化之间保持了平衡，是实现变密度地下水资源多目标设计的一种稳定而稳健的方法。
In this paper, a new hybrid multi‐objective evolutionary algorithm (MOEA), the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), is proposed for the management of groundwater resources under variable density conditions. Relatively few MOEAs can possess global search ability contenting with intensified search in a local area. Moreover, the overall searching ability of tabu search (TS) based MOEAs is very sensitive to the neighborhood step size. The NPTSGA is developed on the thought of integrating the genetic algorithm (GA) with a TS based MOEA, the niched Pareto tabu search (NPTS), which helps to alleviate both of the above difficulties. Here, the global search ability of the NPTS is improved by the diversification of candidate solutions arising from the evolving genetic algorithm population. Furthermore, the proposed methodology coupled with a density‐dependent groundwater flow and solute transport simulator, SEAWAT, is developed and its performance is evaluated through a synthetic seawater intrusion management problem. Optimization results indicate that the NPTSGA offers a tradeoff between the two conflicting objectives. A key conclusion of this study is that the NPTSGA keeps the balance between the intensification of nondomination and the diversification of near Pareto‐optimal solutions along the tradeoff curves and is a stable and robust method for implementing the multi‐objective design of variable‐density groundwater resources.