Case study of solving optimization problems using neural networks

X. Xu; S. Chen; W. T. Tsai; N. K. Huang

doi:10.1016/0893-6080(88)90190-6

Case study of solving optimization problems using neural networks

X. Xu^*
, S. Chen
, W. T. Tsai
, N. K. Huang

^*此作品的通讯作者

University of Minnesota Twin Cities

科研成果: 期刊稿件 › 会议文章 › 同行评审

摘要

This paper studies the performance of Hopfield's neural network also known as the McCulloch-Pitts model, in solving optimization problems. We have discovered that it can not solve many problems satisfactorily including the Traveling Salesman Problem (TSP). But, it can solve some problems quite well, e.g., the Graph Coloring Problem (GCP). Near-optimal solutions can be easily obtained using our methodology, and the performances, contrary to common belief, are not so much affected by the parameters of the energy function, if the parameters are within certain range.

源语言	英语
页（从-至）	151
页数	1
期刊	Neural Networks
卷	1
期	1 SUPPL
DOI	https://doi.org/10.1016/0893-6080(88)90190-6
出版状态	已出版 - 1988
已对外发布	是
活动	International Neural Network Society 1988 First Annual Meeting - Boston, MA, USA 期限: 6 9月 1988 → 10 9月 1988

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title = "Case study of solving optimization problems using neural networks",

abstract = "This paper studies the performance of Hopfield's neural network also known as the McCulloch-Pitts model, in solving optimization problems. We have discovered that it can not solve many problems satisfactorily including the Traveling Salesman Problem (TSP). But, it can solve some problems quite well, e.g., the Graph Coloring Problem (GCP). Near-optimal solutions can be easily obtained using our methodology, and the performances, contrary to common belief, are not so much affected by the parameters of the energy function, if the parameters are within certain range.",

author = "X. Xu and S. Chen and Tsai, \{W. T.\} and Huang, \{N. K.\}",

year = "1988",

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TY - JOUR

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AU - Xu, X.

AU - Chen, S.

AU - Tsai, W. T.

AU - Huang, N. K.

PY - 1988

Y1 - 1988

N2 - This paper studies the performance of Hopfield's neural network also known as the McCulloch-Pitts model, in solving optimization problems. We have discovered that it can not solve many problems satisfactorily including the Traveling Salesman Problem (TSP). But, it can solve some problems quite well, e.g., the Graph Coloring Problem (GCP). Near-optimal solutions can be easily obtained using our methodology, and the performances, contrary to common belief, are not so much affected by the parameters of the energy function, if the parameters are within certain range.

AB - This paper studies the performance of Hopfield's neural network also known as the McCulloch-Pitts model, in solving optimization problems. We have discovered that it can not solve many problems satisfactorily including the Traveling Salesman Problem (TSP). But, it can solve some problems quite well, e.g., the Graph Coloring Problem (GCP). Near-optimal solutions can be easily obtained using our methodology, and the performances, contrary to common belief, are not so much affected by the parameters of the energy function, if the parameters are within certain range.

UR - https://www.scopus.com/pages/publications/0024176103

U2 - 10.1016/0893-6080(88)90190-6

DO - 10.1016/0893-6080(88)90190-6

M3 - 会议文章

AN - SCOPUS:0024176103

SN - 0893-6080

VL - 1

SP - 151

JO - Neural Networks

JF - Neural Networks

IS - 1 SUPPL

T2 - International Neural Network Society 1988 First Annual Meeting

Y2 - 6 September 1988 through 10 September 1988

ER -

Case study of solving optimization problems using neural networks

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