Interval Double-Sided Fuzzy Chance-Constrained Programming Model for Water Resources Allocation

Abstract

In this study, an interval double-sided fuzzy chance-constrained programming (IDFCP) approach is developed for identifying water resources allocation strategies under uncertainty. Through incorporating interval parameter programming, double-sided fuzzy programming, and chance-constrained programming into a general framework, IDFCP can effectively deal with uncertainties expressed as intervals, probability distributions, and fuzzy sets. IDFCP can also examine the risk of violating system constraints. IDFCP is then applied to water resources allocation in the middle and upper reaches of Fen River Basin that is associated with multiuser, multiregion, and multisource features. Interval solutions of the compromise decision alternatives are generated under different scenarios in association with different risk levels of violating constraints (i.e., p levels), fuzzy membership degrees (i.e., α-cut levels), credible degrees (i.e., minimum and maximum), and reclaimed water utilization ratios. Results obtained show that water availability can affect water allocation pattern and system benefit. Results are helpful for decision makers to identify desirable strategies under various environmental and system-credibility constraints in more profitable and sustainable ways.