Search

Due to insufficiency and ineffectiveness of monitoring facilities, variations in natural conditions and changes of human behaviors, watershed planning is interwoven with imprecise data, resulting in a multitude of complexities. A robust interval fuzzy programming approach with superiority–inferiority and risk-aversion analyses (RIFP-SIRA) was developed for identifying sustainable agricultural and industrial production strategies at the watershed scale in a highly uncertain environment. RIFP-SIRA represented a novel attempt to tackle synergies of uncertain information in the forms of intervals with non-statistical bounds and conventional intervals. The developed method was applied to a Chinese watershed. A RIFP-SIRA model was formulated and analyzed under three scenarios to investigate the effects of different policies and standards on watershed development plans. Sensitivity of the model's solutions to varied risk-aversion and input-fluctuation levels were analyzed, verifying the superiority of RIFP-SIRA over the existing inexact approaches. This research revealed that RIFP-SIRA could provide local authorities with robust, yet flexible decision plans. It could enable a quantitative analysis over the trade-offs between the economic benefits and environmental risks in the absence of probabilistic information. [ABSTRACT FROM AUTHOR]

In this study, a feasibility-analysis-based inexact fuzzy multistage model (FA-IFMSM) was developed for supporting the planning of energy and environmental systems under multiform uncertainties. In FA-IFMSM, methods of feasibility-analysis-based fuzzy linear programming (FA-FLP) and inexact multistage stochastic programming (IMSP) with recourse were integrated into a general mixed-integer linear programming framework, such that the developed model could tackle uncertainties described in terms of probability distributions, interval values, fuzzy sets, and their hybrid and mixture. Moreover, it could reflect dynamic features of facility-capacity expansions and energy supplies over a multistage context. It could also quantify constraint violation degrees through the adoption of various acceptable degree levels. Then the proposed model was applied to a regional energy and environmental system to illustrate its applicability, where conventional and renewable energy resources and their economic and environmental implications were considered. The results indicated that reasonable solutions were generated. They were helpful for supporting (1) adjustment or justification of allocation patterns of regional energy resources and services; (2) formulation of local policies regarding energy consumption, economic development, and environmental protection; and (3) in-depth analysis of trade-offs among system cost and satisfaction degree, and environmental requirements under multiple uncertainties. [ABSTRACT FROM AUTHOR]