Bilevel Optimization of Regional Water Resources Allocation Problem under Fuzzy Random Environment

Abstract

The allocation of water resources has long been recognized as a critical optimization problem. In this study, a bilevel programming model with fuzzy random variables is developed for tackling a regional water resources allocation problem on the basis of water rights distribution in a river basin. The bilevel programming model takes the optimal total benefit of the society and the optimal economic benefit of each subarea as the upper and lower targets, respectively. In contrast to previous studies, the balance of the satisfactory degree between the upper and lower decision makers is considered in the bilevel optimization for ensuring the equity of the water resource allocation. To deal with inherent uncertainties, the fuzzy random variables are first transformed into trapezoidal fuzzy numbers, and by taking advantage of the expected value operation, the trapezoidal fuzzy numbers are subsequently defuzzified. For solving the complex and nonlinear bilevel programming model, an interactive fuzzy programming technique and an entropy-Boltzmann selection-based genetic algorithm are designed as a combined solution method. Finally, the results and comparisons analysis of a case study are presented to demonstrate the practicality and efficiency of the optimization method.