title: Inexact rough-interval two-stage stochastic programming for conjunctive water allocation problems.
abstract: An inexact rough-interval two-stage stochastic programming (IRTSP) method is developed for conjunctive water allocation problems. Rough intervals (RIs), as a particular case of rough sets, are introduced into the modeling framework to tackle dual-layer information provided by decision makers. Through embeding upper and lower approximation intervals, rough intervals are capable of reflecting complex parameters with the most reliable and possible variation ranges being identified. An interactive solution method is also derived. A conjunctive water-allocation system is then structured for characterizing the proposed model. Solutions indicate a detailed optimal allocation scheme with a rough-interval form; a total of [[1048.83, 2078.29]:[1482.26, 2020.60]] would be obtained under the pre-regulated inputs. Comparisons of the proposed model to a conventional and an interval two-stage stochastic programming model are also conducted. The results indicate that the optimal objective function values of TSP and ITSP always fall into the range of f(opt)(+/-(UAI)), while they are sometimes out of the range of f(opt)(+/-(LAI)); the optimal solutions of decision variables also present this feature. This implies the reliability of IRTSP in handling conjunctive water allocation problems.
authors.affiliation: EVSE, Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada.
authors.forename: Hongwei
authors.initials: H
authors.lastname: Lu
authors.forename: Guohe
authors.initials: G
authors.lastname: Huang
authors.forename: Li
authors.initials: L
authors.lastname: He
mesh_terms: D008962:Models, Theoretical; D013269:Stochastic Processes; D014881:Water Supply