The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
Joint Authors
Zhang, Tao
Chen, Zhong
Liu, June
Li, Xiong
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-14
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Zhang, Tao& Chen, Zhong& Liu, June& Li, Xiong. 2017. The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1139844
Modern Language Association (MLA)
Zhang, Tao…[et al.]. The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1139844
American Medical Association (AMA)
Zhang, Tao& Chen, Zhong& Liu, June& Li, Xiong. The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1139844
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139844