In this study, an inexact two-stage water management (ITWM) model is developed for planning agricultural irrigation in the Zhangweinan River Basin, China. The ITWM model is derived from the incorporation of interval-parameter programming (IPP) within a two-stage stochastic programming (TSP)...

Greenhouse gas (GHG) concentrations are expected to continue to rise due to the ever-increasing use of fossil fuels and ever-boosting demand for energy. This leads to inevitable conflict between satisfying increasing energy demand and reducing GHG emissions. In this study, an integrated...

In this study, a two-stage inexact-stochastic programming (TISP) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed TISP incorporates techniques of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) within a...

In this study, an inexact fuzzy-stochastic energy model (IFS-EM) is developed for planning energy and environmental systems (EES) management under multiple uncertainties. In the IFS-EM, methods of interval parameter fuzzy linear programming (IFLP) and multistage stochastic programming with...

In this study, an interval full-infinite mixed-integer municipal-scale energy model (IFMI-MEM) is developed for planning energy systems of Beijing. IFMI-MEM is based on an integration of existing interval-parameter programming (IPP), mixed-integer linear programming (MILP) and full-infinite...

In this study, an interval-valued minimax regret analysis (IMRA) method is proposed for planning greenhouse gas (GHG) abatement under uncertainty. The IMRA method is a hybrid of interval-parameter programming (IPP) and minimax regret analysis (MMR) techniques. The developed method is applied to...

In regional water management systems, various uncertainties may be derived from random feature of resource conditions and natural processes, errors in estimated modeling parameters, as well as imprecision or fuzziness human-induced. This leads to difficulties in formulating and solving the...

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...

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, a full-infinite interval-stochastic mixed-integer programming (FIMP) method is developed for planning carbon emission trading (CET) under dual uncertainties. FIMP has advantages in uncertainty reflection and policy analysis, particularly when the input parameters are provided as...