Interactive two-stage stochastic fuzzy programming for water resources management

• Published in: Journal of environmental management Vol. 92; no. 8; pp. 1986 - 1995
• Main Authors: Wang, S., Huang, G.H.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.08.2011; Elsevier; Academic Press Ltd
• Subjects: Algorithms; Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Conservation, protection and management of environment and wildlife; Decision making; Economic efficiency; Fundamental and applied biological sciences. Psychology; Fuzzy; Fuzzy Logic; Fuzzy set theory; General aspects; Interactive; Interactive fuzzy resolution; Interval; Methodology; Policies; Policy analysis; Programming; Resource allocation; Software; Stochastic models; Stochastic Processes; Stochasticity; Studies; Two-stage; Uncertainty; Water management; Water resources; Water resources management; Water Supply; Uncertainty; Water resources management; Two-stage; Policy analysis; Interactive fuzzy resolution; Interval; Policy; Water resource management; Environmental management
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2011.03.024

In this study, an interactive two-stage stochastic fuzzy programming (ITSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact two-stage stochastic programming (ITSP) framework. ITSFP can not only tackle dual uncertainties presented as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints, but also permit in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised policy targets are violated. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees has been generated for planning the water resources allocation. They can help the decision makers (DMs) to conduct in-depth analyses of tradeoffs between economic efficiency and constraint-violation risk, as well as enable them to identify, in an interactive way, a desired compromise between satisfaction degree of the goal and feasibility of the constraints (i.e., risk of constraint violation).