Abstract
This paper presents an interval-parameter two-stage stochastic fuzzy programming with type-2 membership functions (ITSFP-T2MF) approach for supporting water resources management under uncertainty. ITSFP-T2MF is capable not only of dealing with a variety of uncertainties expressed as probability distributions, intervals, and type-2 fuzzy sets, but also of reflecting the complexity of uncertainty presented as the concept of a flexible fuzzy decision. A scenario-based solution method is proposed for solving ITSFP-T2MF, which takes into account different attitudes of decision makers (DMs) towards the objective-function value and constraints. Moreover, the solution method can ensure that no infeasible solutions are included in the results by means of a feasibility test and a constricting algorithm, leading to an enhanced system safety. ITSFP-T2MF is applied to a case study of water resources allocation under uncertainty. The results indicate that interval solutions can be obtained under different scenarios, which enhances the diversity of solutions for supporting the decisions of water resources allocation. Furthermore, a variety of decision alternatives can be generated under different policies for water resources management, which permits an in-depth policy analysis associated with different levels of economic penalties when the promised water-allocation targets are violated, and thus helps DMs identify desired water-allocation plans according to practical situations.
Original language | English |
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Pages (from-to) | 1493-1506 |
Number of pages | 14 |
Journal | Stochastic Environmental Research and Risk Assessment |
Volume | 27 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Aug 2013 |
Externally published | Yes |
Keywords
- Decision-making
- Interval
- Two-stage stochastic programming
- Type-2 fuzzy set
- Uncertainty
- Water resources management
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Chemistry
- Water Science and Technology
- Safety, Risk, Reliability and Quality
- General Environmental Science