Generalized Interval Fuzzy Chance-Constrained Programming Method for Domestic Wastewater Management Under Uncertainty – A Case Study of Kunming, China

In this study, interval mathematical programming (IMP), m λ -measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to a generalized interval fuzzy chance-constrained programming (GIFCP) method. GIFCP can be used to address not only interval...

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Bibliographic Details
Published in:Water resources management 2015-07, Vol.29 (9), p.3015-3036
Main Authors: Dai, C, Cai, Y. P, Liu, Y, Wang, W. J, Guo, H. C
Format: Article
Language:English
Subjects:
Atmospheric Sciences
Capital budgeting
Case studies
China
Civil Engineering
Costs
Credibility
Domestic wastewater
Earth and Environmental Science
Earth Sciences
Environment
Environmental protection
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrology/Water Resources
inosine monophosphate
Intervals
Long term planning
Mathematical analysis
Mathematical programming
Objective function
Optimization
Pessimism
planning
Programming
risk
Studies
Uncertainty
Variables
wastewater
Wastewater management
Water bodies
Water resources management
Water treatment
Water treatment plants
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Summary:In this study, interval mathematical programming (IMP), m λ -measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to a generalized interval fuzzy chance-constrained programming (GIFCP) method. GIFCP can be used to address not only interval uncertainties in the objective function, variables and left-hand side parameters but also fuzzy uncertainties on the right-hand side. Also, it can reflect the aspiration preference of optimistic and pessimistic decision makers due to the integration of m λ -measure. The developed method is applied to the long-term planning of a domestic wastewater management system in the city of Kunming, China, with consideration of the eco-environmental protection of downstream water body. The solution results of the GIFCP method can generate a series of optimal wastewater allocation patterns and WTPs capacity expansion schemes under different risk levels, provide in-depth insights into the effects of uncertainties, and consider the proper balance between system cost and risk of constraint violation.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-014-0902-x