A dual-interval vertex analysis method and its application to environmental decision making under uncertainty

Journal of the Air & Waste Management Association

Veawab

2011

In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO 2 ) control planning model to identify effective SO 2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO 2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP, and then identify desired policies for SO 2 -emission control under uncertainty.Implications: The GFLP method is effective in addressing air quality management planning associated with fuzzy parameter in the constraints and objective. The stepwise interactive algorithm proposed to solving the GFLP model would not lead to complicated intermediate submodels. Thus it would be much applicable for large-scale air quality management problems. The applications of the method can help decision makers in (i) generating allocation schemes for SO 2 emissions; (ii) identifying the plausibility of each allocation alternative; and (iii) estimating the total costs of different SO 2 emission control policies.

Section: Overview Of the Study Systemmentioning

confidence: 99%

Section: Overview Of the Study Systemmentioning

confidence: 99%

“…The objective is to minimize the total cost for SO 2 abatement. Thus, the optimization model of a regional air quality management model can be formulated as (Li et al, 2010):…”

Section: Formulation Of Gflp Model For Air Quality Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A generalized fuzzy linear programming approach for environmental management problem under uncertainty

Fan

Journal of the Air & Waste Management Association

Veawab

2011

Technology evaluation and decision making for sustainability enhancement of industrial systems under uncertainty

Liu

2012

AIChE Journal

Technology‐based sustainability enhancement is a key approach for industrial sustainability realization. However, identification of effective technologies for any industrial system could be very challenging. If the available data and information about the industrial system and technologies are incomplete, imprecise, and uncertain, then technology identification could be very difficult. In this article, the authors introduce a simple, yet systematic interval‐parameter‐based methodology for identifying quickly superior solutions under uncertainty for sustainability performance improvement. The methodology is general enough for the study of sustainability enhancement problems of any size and scope. A case study on sustainable development of biodiesel manufacturing demonstrates methodological efficacy. © 2012 American Institute of Chemical Engineers AIChE J, 58: 1841–1852, 2012

A fuzzy‐based simulation method for modelling hydrological processes under uncertainty

Chen

et al. 2010

Hydrological Processes

Abstract:In this study, a fuzzy-based simulation method (FBSM) is developed for modelling hydrological processes associated with vague information through coupling fuzzy vertex analysis technique with distributed hydrological model. The FBSM can handle uncertainties existed as fuzzy sets in the hydrological modelling systems, and solutions under an associated number of˛-cut levels can be generated by solving 2 n deterministic models. The lower reach of the Tarim River Basin in China is selected as a study case for demonstrating applicability of the proposed method. The developed model is calibrated and validated against observed groundwater elevation for four wells during the period 2000-2001, and generally performed acceptable for model Nash-Sutcliffe coefficient (R2) and correlation coefficient (R). The R2 is approximately over 0Ð65 and the correlation coefficient is higher than 0Ð90. Based on the technique of fuzzy simulation, the uncertainties of two parameters (K H and LC) are reflected under different˛-cut levels. The results indicate that, under a lower degree of plausibility, the interval between the lower and upper bounds of the groundwater elevation is wider; conversely, a higher degree of plausibility would lead to a narrow interval. The main effect of K H is more significant than the effect of LC at most well sites. The proposed method is useful for studying hydrological processes within a system containing multiple factors with uncertainties and providing support for identifying proper water resources management strategies.