The Multi-Objective Differential Evolutionary Algorithms and its Application in Optimal Allocation of Water Resources

Yan Hong Long; Li Yang Yu

doi:10.4028/www.scientific.net/AMR.518-523.4093

Paper Titles

Application of Ultrasonic Bathometer for Muddy-Water to Intellectual Detection of Root-Stone in the Yellow River
p.4074

Calculation of Water Environmental Capacity for a Eutrophicated Reservoir
p.4078

Experimental and Theoretical Studies on Effects of Heterogeneity on Channeling in Waterflooding
p.4084

Study on Ecological Water Table in a Reclaimed Water Irrigation Area in the North China Plain
p.4088

The Multi-Objective Differential Evolutionary Algorithms and its Application in Optimal Allocation of Water Resources
p.4093

To Classify the Groundwater Hydrographs by Factor Analysis Method
p.4097

Advancement in Research of Hydrological Processes Simulation for Karst Region and Future Challenges
p.4104

Analysis and Comparison on Typical Methods for Predicting Composite Roughness of River
p.4111

Analysis of Hydrological Data Based on BP Neural Network Approximation and Polynomial Fitting
p.4115

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 518-523The Multi-Objective Differential Evolutionary...

The Multi-Objective Differential Evolutionary Algorithms and its Application in Optimal Allocation of Water Resources

Abstract:

Abstract: Differential evolution algorithm (differential evolution DE) is a multi-objective evolutionary algorithm based on groups， which instructs optimization search by swarm intelligence produced by co-operation and competition among individuals within groups. This paper presents it to the research of optimal allocation of water resources. Accord to the application of the example, the results shows that reasonable and effective.

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Periodical:

Advanced Materials Research (Volumes 518-523)

Pages:

4093-4096

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.518-523.4093

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Online since:

May 2012

Authors:

Yan Hong Long, Li Yang Yu

Keywords:

DE, Differential Evolution, Optimal Allocation, Swarm Intelligence, Water Resource

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