fuzzy-dependent chance multi-objective programming for water resources planning of a coastal city under fuzzy environment

A fuzzy multi-objective water resources management model is developed to determine the satisfactory water allocation plan in a coastal city of Northeast China. The imprecise predicted values of parameters are represented by fuzzy numbers, and seven fuzzy objectives of maximizing the possibilities of...

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Bibliographic Details
Published in:Water and environment journal : WEJ Vol. 25; no. 1; pp. 40 - 54
Main Authors: Peng, Hui, Zhou, Huicheng
Format: Journal Article
Language:English
Published: Oxford, UK Blackwell Publishing Ltd 01.03.2011
Wiley Subscription Services, Inc
Subjects:
algorithms
China
Dalian City
fuzzy logic
fuzzy numbers
fuzzy simulation
fuzzy-dependent chance multi-objective programming
genetic algorithm
Surface water
Surface-groundwater relations
urban planning
Water allocation
water requirement
Water requirements
Water resources management
water resources planning
water supply
China
China, People's Rep
ISSN:1747-6585, 1747-6593
Online Access:Get full text
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Summary:A fuzzy multi-objective water resources management model is developed to determine the satisfactory water allocation plan in a coastal city of Northeast China. The imprecise predicted values of parameters are represented by fuzzy numbers, and seven fuzzy objectives of maximizing the possibilities of satisfying the water requirements for six users and total cost less than the expected value are considered. After weighted summation method (WSM) is used to transform the multi-objective model into a single-objective model, the satisfactory water allocation plan is efficiently derived according to decision makers' preferences by using a hybrid solution procedure of combining genetic algorithm with fuzzy simulation technique. Results of sensitivity test imply that the interval [0.2, 0.6] of cutting level, surface water and groundwater supplies have the most sensitive influence on results of the model. Moreover, results of discussion demonstrate that the assumption of linearity can be accepted, and membership function of fuzzy number has little influence on results of the model.
Bibliography:http://dx.doi.org/10.1111/j.1747-6593.2009.00187.x
istex:1B359087A80B03C62FA2720A60578018C03DD16E
ArticleID:WEJ187
ark:/67375/WNG-11QR904R-L
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SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1747-6585
1747-6593
DOI:10.1111/j.1747-6593.2009.00187.x