A Hybrid Multi-Objective Evolutionary Algorithm for Optimal Groundwater Management under Variable Density Conditions

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 conte...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Acta geologica Sinica (Beijing) Jg. 86; H. 1; S. 246 - 255
Hauptverfasser:	Yun, YANG, Jianfeng, WU, Xiaomin, SUN, Jin, LIN, Jichun, WU
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford, UK Blackwell Publishing Ltd 01.02.2012 Wiley Subscription Services, Inc Department of Hydrosciences, School of Earth Sciences and Engineering, Nanjing University, Nanjing,Jiangsu 210093, China%Nanfing Hydraulic Research Institute, Nanfing, Jiangsu 210029, China
Ausgabe:	English ed.
Schlagworte:	Algorithms Coastal aquifers Density Evolutionary algorithms genetic algorithm Genetic algorithms Groundwater Groundwater flow Groundwater management Heuristic multi-objective optimization niched Pareto tabu search niched Pareto tabu search combined with genetic algorithm Optimization Pareto optimality Saline water intrusion Searching Seawater seawater intrusion Solute transport Tabu search Water resources 优化全局搜索能力地下水管理地下水资源管理多目标进化算法度条件混合禁忌搜索 genetic algorithm multi-objective optimization niched Pareto tabu search combined with genetic algorithm niched Pareto tabu search seawater intrusion
ISSN:	1000-9515, 1755-6724
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!