GLOBAL SOLUTION OF NONLINEAR BILEVEL PROGRAMMING PROBLEMS BASED ON SIMULATED ANNEALING AND NEURAL NETWORK

摘要

A new method for solving a class of nonlinear bilevel programming problems is proposed in this paper which combines the accelerated simulated annealing algorithm and the nonlinear programming neural network in an appropriate manner. To cope with the explicitly defined high-level constraints depending only on the high-level variables, an auxiliary optimization problem is introduced at the upper level, avoiding using the penalty function method to deal with such constraints. The computational results for numerical examples illustrate the validity and better performance of the proposed method in terms of solution quality and computational efficiency.