A Hybrid Intelligent Algorithm for Stochastic Multilevel Programming

摘要

In this paper, a decentralized decision-making problem in stochastic environment is formulated as expected value multilevel programming, and chance-constrained multilevel programming according to different decision criteria. In order to solve the proposed stochastic multilevel programming models for finding the Stackelberg-Nash equilibrium, genetic algorithm, neural network and stochastic simulation are integrated to produce a hybrid intelligent algorithm. Finally, two numerical examples are provided to illustrate the effectiveness of the hybrid intelligent algorithm.