An Interval-Parameter Multi-stage Stochastic Chance-Constrained Mixed Integer Programming Model for Inter-basin Water Resources Management Systems under Uncertainty

Abstract

In this study, an interval-parameter multi-stage stochastic chance-constrained mixed integer programming (IMSCMIP) method has been developed for inter-basin water resources management systems under uncertainty. By incorporating the chance-constrained programming (CCP) techniques, and mixed integer programming within an interval-parameter multi-stage stochastic programming framework, the model improves upon the interval-parameter multi-stage stochastic programming (IMSP) and can deal with uncertainties expressed as not only possibility and probabilities distributions but also as discrete intervals, and can incorporate pre-defined water policies directly into its optimization process. A multilayer scenario tree is used to tackle the uncertainties expressed as probability distributions and discrete intervals in IMSCMIP.