title: A two-stage fuzzy chance-constrained water management model.
abstract: In this study, an inexact two-stage fuzzy gradient chance-constrained programming (ITSFGP) method is developed and applied to the water resources management in the Heshui River Basin, Jiangxi Province, China. The optimization model is established by incorporating interval programming, two-stage stochastic programming, and fuzzy gradient chance-constrained programming within an optimization framework. The hybrid model can address uncertainties represented as fuzzy sets, probability distributions, and interval numbers. It can effectively tackle the interactions between pre-regulated economic targets and the associated environmental penalties attributed to water allocation schemes and reflect the tradeoffs between economic revenues and system-failure risk. Furthermore, uncertainties associated with the decision makers' preferences are considered in decision-making processes. The obtained results can provide decision support for the local sustainable economic development and water resources allocation strategies under multiple uncertainties.
authors.affiliation: Faculty of Engineering and Applied Science, University of Regina, Regina, SK, S4S 0A2, Canada.
authors.forename: Jiaxuan
authors.initials: J
authors.lastname: Xu
authors.affiliation: Faculty of Engineering and Applied Science, University of Regina, Regina, SK, S4S 0A2, Canada. huangg@uregina.ca.
authors.forename: Guohe
authors.initials: G
authors.lastname: Huang
authors.affiliation: Department of Civil Engineering, McMaster University, Hamilton, ON, L8S 4L8, Canada.
authors.forename: Zoe
authors.initials: Z
authors.lastname: Li
authors.affiliation: Faculty of Engineering and Applied Science, University of Regina, Regina, SK, S4S 0A2, Canada.
authors.forename: Jiapei
authors.initials: J
authors.lastname: Chen
mesh_terms: D002681:China; D017143:Fuzzy Logic; D008962:Models, Theoretical; D013269:Stochastic Processes; D035501:Uncertainty; D014867:Water
chemical_list: D014867:Water
keywords: Chance-constrained programming; Fuzzy gradient; Optimization modeling; Stochastic programming; Uncertainty; Water resources management