Global Solution of Hierarchical Optimal Control Problems Based on Simulated Annealing and Neural Networks

Abstract

A new method for solving hierarchical optimal control problems is proposed in this paper which combines the accelerated simulated annealing algorithm and the constrained optimal control neural network in an appropriate manner. Two different forms of explicitly defined high-level constraints of the hierarchical problems are treated by the different methods. To cope with the high-level constraints depending only on the high-level control variables, an auxiliary problem is introduced at the upper level, avoiding using the penalty function method to deal with such constraints in an inefficient way. The computational results for numerical examples demonstrate the validity and better performance of the proposed method in terms of solution quality and computational efficiency.