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

Jingru Li; Junzo Watada; Shamshul Bahar Yaakob

doi:10.1109/IJCNN.2014.6889483

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

Jingru Li^*, Junzo Watada, Shamshul Bahar Yaakob

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Proceedings of the International Joint Conference on Neural Networks
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	382-389
Number of pages	8
ISBN (Print)	9781479914845
DOIs	https://doi.org/10.1109/IJCNN.2014.6889483
Publication status	Published - 2014 Sept 3
Event	2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing Duration: 2014 Jul 6 → 2014 Jul 11

Other

Other	2014 International Joint Conference on Neural Networks, IJCNN 2014
City	Beijing
Period	14/7/6 → 14/7/11

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.2014.6889483

Cite this

A genetic algorithm based double layer neural network for solving quadratic bilevel programming problem. / Li, Jingru; Watada, Junzo; Yaakob, Shamshul Bahar.
Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc., 2014. p. 382-389 6889483.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, J, Watada, J & Yaakob, SB 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., 6889483, Institute of Electrical and Electronics Engineers Inc., pp. 382-389, 2014 International Joint Conference on Neural Networks, IJCNN 2014, Beijing, 14/7/6. https://doi.org/10.1109/IJCNN.2014.6889483

@inproceedings{f221e21c080243288a317a5f711a4f52,

title = "A genetic algorithm based double layer neural network for solving quadratic bilevel programming problem",

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.",

author = "Jingru Li and Junzo Watada and Yaakob, {Shamshul Bahar}",

year = "2014",

month = sep,

day = "3",

doi = "10.1109/IJCNN.2014.6889483",

language = "English",

isbn = "9781479914845",

pages = "382--389",

booktitle = "Proceedings of the International Joint Conference on Neural Networks",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2014 International Joint Conference on Neural Networks, IJCNN 2014 ; Conference date: 06-07-2014 Through 11-07-2014",

}

TY - GEN

T1 - A genetic algorithm based double layer neural network for solving quadratic bilevel programming problem

AU - Li, Jingru

AU - Watada, Junzo

AU - Yaakob, Shamshul Bahar

PY - 2014/9/3

Y1 - 2014/9/3

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84908470045&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84908470045&partnerID=8YFLogxK

U2 - 10.1109/IJCNN.2014.6889483

DO - 10.1109/IJCNN.2014.6889483

M3 - Conference contribution

AN - SCOPUS:84908470045

SN - 9781479914845

SP - 382

EP - 389

BT - Proceedings of the International Joint Conference on Neural Networks

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 International Joint Conference on Neural Networks, IJCNN 2014

Y2 - 6 July 2014 through 11 July 2014

ER -

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

Abstract

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this