A hybrid intelligent algorithm for solving the bilevel programming models

Abstract

In this paper, genetic algorithm (GA) and neural network (NN) are integrated to produce a hybrid intelligent algorithm for solving the bilevel programming models. GA is used to select a set of potential combination from the entire generated combination. Then a meta-controlled Boltzmann machine which is formulated by comprising a Hopfield network and a Boltzmann machine (BM) is used to effectively and efficiently determine the optimal solution. The proposed method is used to solve the examples of bilevel programming for two- level investment in a new facility. The upper layer will decide the optimal company investment. The lower layer is used to decide the optimal department investment. Typical application examples are provided to illustrate the effectiveness and practicability of the hybrid intelligent algorithm.