Asymmetric Neural Network and Its Application to Knapsack Problem
Summary :
We propose an asymmetric neural network which can solve inequality-constrained combinatorial optimization problems that are difficult to solve using symmetric neural networks. In this article, a knapsack problem that is one of such the problem is solved using the proposed network. Additionally, we study condition for obtaining a valid solution. In computer simulations, we show that the condition is correct and that the proposed network produces better solutions than the simple greedy algorithm.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E78-A No.3 pp.300-305
- Publication Date
- 1995/03/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section of Selected Papers from the 7th Karuizawa Workshop on Circuits and Systems)
- Category
- Neural Networks
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Keyword
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Akira YAMAMOTO, Masaya OHTA, Hiroshi UEDA, Akio OGIHARA, Kunio FUKUNAGA, "Asymmetric Neural Network and Its Application to Knapsack Problem" in IEICE TRANSACTIONS on Fundamentals,
vol. E78-A, no. 3, pp. 300-305, March 1995, doi: .
Abstract: We propose an asymmetric neural network which can solve inequality-constrained combinatorial optimization problems that are difficult to solve using symmetric neural networks. In this article, a knapsack problem that is one of such the problem is solved using the proposed network. Additionally, we study condition for obtaining a valid solution. In computer simulations, we show that the condition is correct and that the proposed network produces better solutions than the simple greedy algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e78-a_3_300/_p
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@ARTICLE{e78-a_3_300,
author={Akira YAMAMOTO, Masaya OHTA, Hiroshi UEDA, Akio OGIHARA, Kunio FUKUNAGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Asymmetric Neural Network and Its Application to Knapsack Problem},
year={1995},
volume={E78-A},
number={3},
pages={300-305},
abstract={We propose an asymmetric neural network which can solve inequality-constrained combinatorial optimization problems that are difficult to solve using symmetric neural networks. In this article, a knapsack problem that is one of such the problem is solved using the proposed network. Additionally, we study condition for obtaining a valid solution. In computer simulations, we show that the condition is correct and that the proposed network produces better solutions than the simple greedy algorithm.},
keywords={},
doi={},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - Asymmetric Neural Network and Its Application to Knapsack Problem
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 300
EP - 305
AU - Akira YAMAMOTO
AU - Masaya OHTA
AU - Hiroshi UEDA
AU - Akio OGIHARA
AU - Kunio FUKUNAGA
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E78-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 1995
AB - We propose an asymmetric neural network which can solve inequality-constrained combinatorial optimization problems that are difficult to solve using symmetric neural networks. In this article, a knapsack problem that is one of such the problem is solved using the proposed network. Additionally, we study condition for obtaining a valid solution. In computer simulations, we show that the condition is correct and that the proposed network produces better solutions than the simple greedy algorithm.
ER -
English
