Showing 11 - 20 of 31
In this study, an IFJMP (interval-parameter full-infinite joint-probabilistic mixed-integer programming) method is developed for supporting EPS (electric power systems) management. The IFJMP-EPS model cannot only deal with uncertainties expressed as joint probabilities, crisp interval values and...
Persistent link: https://www.econbiz.de/10011054533
In this study, a dual-interval vertex analysis (DIVA) method is developed, through incorporating the vertex method within an interval-parameter programming framework. The developed DIVA method can tackle uncertainties presented as dual intervals that exist in the objective function and the left-...
Persistent link: https://www.econbiz.de/10005023381
A hybrid fuzzy-stochastic water-management (FSWM) model is developed for agricultural sustainability under uncertainty, based on advancement of a multistage fuzzy-stochastic quadratic programming (MFSQP) approach. In MFSQP, uncertainties presented in terms of fuzziness and randomness can be...
Persistent link: https://www.econbiz.de/10008484623
In this study, a two-stage fuzzy robust integer programming (TFRIP) method has been developed for planning environmental management systems under uncertainty. This approach integrates techniques of robust programming and two-stage stochastic programming within a mixed integer linear programming...
Persistent link: https://www.econbiz.de/10005337260
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...
Persistent link: https://www.econbiz.de/10009249249
An integrated optimization method is developed for supporting agriculture water management and planning in Tarim River Basin, Northwest China. The developed method couples two-stage stochastic programming (TSP) with inexact quadratic program (IQP). The hydrological model is provided for...
Persistent link: https://www.econbiz.de/10010572987
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...
Persistent link: https://www.econbiz.de/10008916440
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...
Persistent link: https://www.econbiz.de/10008916514
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...
Persistent link: https://www.econbiz.de/10008917097
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...
Persistent link: https://www.econbiz.de/10008919378