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...

In this research, a simulation-based fuzzy possibilistic programming (SFPP) model was advanced through integrating California puff (CALPUFF), fuzzy sets theory and inexact optimization within a general framework. It has advantages in uncertainty reflection, pollutant dispersion modeling, and the...

In this study, a multistage stochastic inexact chance-constraint programming (MSICCP) model is developed for power supply management under uncertainties. In the MSICCP model, methods of multistage stochastic programming (MSP), interval-parameter programming (IPP), and chance-constraint...

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...

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 paper a stochastic robust optimization problem of residential micro-grid energy management is presented. Combined cooling, heating and electricity technology (CCHP) is introduced to satisfy various energy demands. Two-stage programming is utilized to find the optimal installed capacity...