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

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 wh...

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Detalles Bibliográficos
Autores principales: Zhang, Tao, Chen, Zhong, Liu, June, Li, Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5618751/
https://www.ncbi.nlm.nih.gov/pubmed/29312446
http://dx.doi.org/10.1155/2017/1853131
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author Zhang, Tao
Chen, Zhong
Liu, June
Li, Xiong
author_facet Zhang, Tao
Chen, Zhong
Liu, June
Li, Xiong
author_sort Zhang, Tao
collection PubMed
description 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.
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spelling pubmed-56187512018-01-08 The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem Zhang, Tao Chen, Zhong Liu, June Li, Xiong Comput Intell Neurosci Research Article 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. Hindawi 2017 2017-09-14 /pmc/articles/PMC5618751/ /pubmed/29312446 http://dx.doi.org/10.1155/2017/1853131 Text en Copyright © 2017 Tao Zhang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Tao
Chen, Zhong
Liu, June
Li, Xiong
The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title_full The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title_fullStr The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title_full_unstemmed The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title_short The Artificial Neural Networks Based on Scalarization Method for a Class of Bilevel Biobjective Programming Problem
title_sort artificial neural networks based on scalarization method for a class of bilevel biobjective programming problem
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5618751/
https://www.ncbi.nlm.nih.gov/pubmed/29312446
http://dx.doi.org/10.1155/2017/1853131
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