An interactive inexact fuzzy bounded programming (IFBP) approach is developed through introducing the concept of fuzzy bounded intervals into an interactive fuzzy compromise programming framework. It can provide decision support for decision makers with conflicting desires of greater objective...

An inexact two-stage fuzzy-stochastic programming (ITFSP) method is developed for water resources management under uncertainty. Fuzzy sets theory is introduced to represent various punishment policies under different water availability conditions. As an extension of conventional two-stage...

In this study, an interval-parameter two-stage stochastic semi-infinite programming (ITSSP) method was developed for water resources management under uncertainty. As a new extension of mathematical programming methods, the developed ITSSP approach has advantages in uncertainty reflection and...

A simulation-based inexact rough-interval programming approach is proposed for agricultural irrigation management in a China’s rural region. The conjunctive use of multiple water sources is examined under a set of land-area, water-availability, environmental-standard, capital, and technical...

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 recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a...

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...

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 inexact optimization modeling approach (IBEM: inexact Beijing energy model) was developed for supporting energy systems planning and air pollution mitigation under uncertainty. This model was based on the integration of multiple inexact optimization techniques, including...