A Fuzzy Robust Nonlinear Programming Model for Stream Water Quality Management

An interval-parameter fuzzy robust nonlinear programming (IFRNP) approach was developed for stream water quality management under uncertainty. The interval and fuzzy robust programming methods were incorporated within a general framework to address uncertainties associated with the nonlinear objecti...

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Bibliographic Details
Published in:Water resources management Vol. 23; no. 14; pp. 2913 - 2940
Main Authors: Zhu, H., Huang, G. H., Guo, P., Qin, X. S.
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.11.2009
Springer
Springer Nature B.V
Subjects:
Atmospheric Sciences
Case studies
China
Civil Engineering
cost effectiveness
Creeks & streams
Earth and Environmental Science
Earth Sciences
Earth, ocean, space
Environment
Environmental impact
Exact sciences and technology
Freshwater
Fuzzy sets
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrology. Hydrogeology
Hydrology/Water Resources
Linear programming
Nonlinear programming
Optimization
Optimization techniques
Quality management
rivers
Simulation
Stream water
streams
Studies
uncertainty
wastewater
Wastewater discharges
Water quality
Water quality management
Water resources
Water resources management
Water treatment
Far East
Asia
China
Anhui China
China, People's Rep., Anhui Prov
Dual uncertainty
Robust
Water quality
Environment
Management
Nonlinear programming
Fuzzy set
Optimization
Interval
rivers
models
cost
fuzzy sets
geologic sections
streams
water quality
optimization
discharge
water resource management
interval
methodology
ISSN:0920-4741, 1573-1650
Online Access:Get full text
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Description
Summary:An interval-parameter fuzzy robust nonlinear programming (IFRNP) approach was developed for stream water quality management under uncertainty. The interval and fuzzy robust programming methods were incorporated within a general framework to address uncertainties associated with the nonlinear objective and the left- and right-hand sides of the constraints. A piecewise linearization approach was developed to deal with the nonlinear cost function. IFRNP could explicitly address complexities of various system uncertainties, where parameters were represented as both interval numbers and fuzzy membership functions. Furthermore, the dual uncertain information associated with the lower and upper bounds of each interval parameter could be effectively tackled through the concept of fuzzy boundary interval. The proposed IFRNP method was applied to a case of water quality management in the Guoyang section of the Guo River in Anhui province, China. A number of cost-effective schemes for water quality management were generated, and allowable wastewater discharge amounts were recommended. The results indicated that IFRNP was applicable to water quality management problems, where high nonlinearities and dual uncertainties exist.
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-009-9416-3