Patrick M. Reed focuses on Mathematical optimization, Multi-objective optimization, Evolutionary algorithm, Water resources and Genetic algorithm. His Mathematical optimization research focuses on subjects like Sampling, which are linked to Kriging. His Multi-objective optimization research incorporates elements of Visualization, Decision support system and Artificial intelligence.
His studies in Evolutionary algorithm integrate themes in fields like Evolutionary computation, Hydrological modelling, Management science and Benchmark. His Water resources research integrates issues from Environmental resource management and Water supply. His Water supply research is multidisciplinary, incorporating elements of Robust decision-making and Operations research.
His primary areas of investigation include Mathematical optimization, Evolutionary algorithm, Multi-objective optimization, Water supply and Environmental resource management. Patrick M. Reed has included themes like Sampling and Sobol sequence, Sensitivity in his Mathematical optimization study. The concepts of his Evolutionary algorithm study are interwoven with issues in Management science and Benchmark.
His research on Management science frequently connects to adjacent areas such as Risk analysis. His work in Multi-objective optimization tackles topics such as Genetic algorithm which are related to areas like Sorting. His research investigates the link between Water supply and topics such as Water resources that cross with problems in Operations research.
Patrick M. Reed mainly focuses on Water supply, Environmental resource management, Drainage basin, Water resource management and Mathematical optimization. His study explores the link between Water supply and topics such as Environmental economics that cross with problems in Investment, Streamflow and Water infrastructure. Patrick M. Reed usually deals with Drainage basin and limits it to topics linked to Flood myth and Parametric statistics, Water balance and Multi reservoir.
His work deals with themes such as Water scarcity, Groundwater, Interoperability, Adaptive management and Hydrology, which intersect with Water resource management. As part of the same scientific family, Patrick M. Reed usually focuses on Hydrology, concentrating on Financial risk and intersecting with Natural resource economics, Evolutionary algorithm and Portfolio. His Multi-objective optimization and Reservoir operation study in the realm of Mathematical optimization connects with subjects such as Space.
Patrick M. Reed mostly deals with Water supply, Environmental resource management, Robustness, Multi-objective optimization and Mathematical optimization. The Water supply study combines topics in areas such as Environmental economics and Decision rule. His Environmental resource management research incorporates themes from Water scarcity, Drainage basin, Land cover, Complex system and Robustness.
His studies deal with areas such as Risk analysis, Joint and Reservoir operation as well as Robustness. The various areas that Patrick M. Reed examines in his Multi-objective optimization study include Control, Stochastic control and Control theory, Sensitivity. His research in Mathematical optimization intersects with topics in Reduction methods and Representation.
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Borg: An auto-adaptive many-objective evolutionary computing framework
David Hadka;Patrick Reed.
State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management
John Nicklow;Patrick Reed;Dragan Savic;Tibebe Dessalegne.
Evolutionary algorithms and other metaheuristics in water resources
H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
Evolutionary multiobjective optimization in water resources: The past, present, and future
Patrick M. Reed;David Hadka;Jonathan D. Herman;Joseph R. Kasprzyk.
Many objective robust decision making for complex environmental systems undergoing change
Joseph R. Kasprzyk;Shanthi Nataraj;Patrick M. Reed;Robert J. Lempert.
Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design
J.B. Kollat;P.M. Reed.
Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation
Y. Tang;Patrick Reed;Thorsten Wagener;K. van Werkhoven.
How should robustness be defined for water systems planning under change
Jonathan D. Herman;Patrick M. Reed;Harrison B. Zeff;Gregory W. Characklis.
How effective and efficient are multiobjective evolutionary algorithms at hydrologic model calibration
Y Tang;P Reed;Thorsten Wagener.
Diagnostic assessment of search controls and failure modes in many-objective evolutionary optimization
David Hadka;Patrick Reed.
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