The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem.

Journal: Computational intelligence and neuroscience
Published Date: Jan 1, 2017

Abstract

A two-stage artificial neural network (ANN) based on scalarization method is proposed for bilevel biobjective programming problem (BLBOP). The induced set of the BLBOP is firstly expressed as the set of minimal solutions of a biobjective optimization problem by using scalar approach, and then the whole efficient set of the BLBOP is derived by the proposed two-stage ANN for exploring the induced set. In order to illustrate the proposed method, seven numerical examples are tested and compared with results in the classical literature. Finally, a practical problem is solved by the proposed algorithm.

Authors

  • Tao Zhang
    Department of Traumatology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, 40044, People's Republic of China.
  • Zhong Chen
    Institute of HIV/AIDS The First Hospital of Changsha, Changsha, China.
  • June Liu
    School of Management, Huaibei Normal University, Huaibei 235000, China.
  • Xiong Li
    School of Software, East China Jiaotong University, Nanchang, 330013, China.

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