Interval-Parameter Linear Optimization Model with Stochastic Vertices for Land and Water Resources Allocation Under Dual Uncertainty

Abstract

Abstract

An interval-parameter linear optimization model with stochastic vertices has been developed, which can be used to deal with dual uncertainties presented as interval-parameter with stochastic vertices that exist in objective function and constraints. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network has been proposed for solving the transformed two submodels from the developed model. The developed model was then applied to the optimization of land and water resources uses among different crops in the Hetao irrigation region, which is the third largest agriculture irrigation area in China with water from only the Yellow River. Various schemes of land and water resources allocation, which are associated with different scenarios of water transferred from the Yellow River, were obtained from the developed model using the hybrid intelligent algorithm. Results indicate that land uses for high-water-demand crops are gradually being transferred into those for low-water-demand crops with decrease of water transferred from the Yellow River. Application of the developed methodology shows that it is an effective method to deal with dual uncertainty in a land-use and water resources management system. The developed method combines advantages of both stochastic programming and interval-parameter programming.