In this study, IMP (interval mathematical programming), mλ-measure, and fuzzy chance-constrained programming are incorporated into a general optimization framework, leading to an IMFCP (interval-parameter mλ-measure based fuzzy chance-constrained programming) method. The IMFCP method can be...

Agricultural nonpoint sources (NPS) pollution has long been regarded as the leading challenge in maintaining water quality of receiving water bodies. Effluent trading can serve as a cost-effective way to achieve optimal configuration of discharge permits in agricultural NPS pollution control....

In this study, a fuzzy-interval possibilistic programming (FIPP) method is developed for supporting sustainable electric power system (EPS) planning with carbon emission abatement under uncertainty. In FIPP, systematic uncertainties expressed as crisp intervals and fuzzy-boundary intervals can...

In this study, a hybrid fuzzy-stochastic programming method is developed for planning water trading under uncertainties of randomness and fuzziness. The method can deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle...

In this study, an interval-robust nonlinear optimization (IRNO) method is developed for planning energy system and managing CO2 emissions with trading scheme, through incorporating interval-parameter programming (IPP) within a robust optimization (RO) framework. In the modeling formulation, two...

The growing concern for global warming caused by the increased atmospheric concentration of carbon dioxide (CO2) has a significant effect on environmental and energy policies and economic activities, due to the ever-increasing use of fossil fuels such as coal, oil and natural gas throughout the...

An interval-parameter chanced-constrained full-infinite mixed-integer programming (ICFMP) approach is proposed for planning energy systems under functional interval uncertainties. ICFMP cannot only deal with crisp intervals, functional intervals, and probability distributions, but also support...

In this study, an IFTSP (interval-fuzzy two-stage stochastic programming) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed IFTSP incorporates techniques of interval fuzzy linear programming and two-stage stochastic programming within a...

In this study, an interval fixed-mix stochastic programming (IFSP) model is developed for greenhouse gas (GHG) emissions reduction management under uncertainties. In the IFSP model, methods of interval-parameter programming (IPP) and fixed-mix stochastic programming (FSP) are introduced into an...

Non-point source (NPS) pollution from agricultural lands has aroused widespread concerns throughout the world. In this study, an interval fuzzy two-stage stochastic non-point source pollution mitigation (IFTNS) model was developed for agricultural systems management under uncertainty through...