A genetic algorithm based double layer neural network for solving quadratic bilevel programming problem

Jingru Li, Junzo Watada, Shamshul Bahar Yaakob

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In this paper, an intelligent genetic algorithm (IGA) and a double layer neural network (NN) are integrated into a hybrid intelligent algorithm for solving the quadratic bilevel programming problem. The intelligent genetic algorithm is used to select a set of potential solution combinations from the entire generated combinations of the upper level. Then a meta-controlled Boltzmann machine, which is formulated by comprising the Hopfield model (HM) and the Boltzmann machine (BM), is used to effectively and efficiently determine the optimal solution of the lower level. Numerical experiments on examples show that the genetic algorithm based double layer neural network enables us to efficiently and effectively solve quadratic bilevel programming problems.

    Original languageEnglish
    Title of host publicationProceedings of the International Joint Conference on Neural Networks
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages382-389
    Number of pages8
    ISBN (Print)9781479914845
    DOIs
    Publication statusPublished - 2014 Sep 3
    Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing
    Duration: 2014 Jul 62014 Jul 11

    Other

    Other2014 International Joint Conference on Neural Networks, IJCNN 2014
    CityBeijing
    Period14/7/614/7/11

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    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

    Cite this

    Li, J., Watada, J., & Yaakob, S. B. (2014). A genetic algorithm based double layer neural network for solving quadratic bilevel programming problem. In Proceedings of the International Joint Conference on Neural Networks (pp. 382-389). [6889483] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2014.6889483