IEICE TRANSACTIONS on Fundamentals
An Evolutionary Algorithm Approach to the Design of Minimum Cost Survivable Networks with Bounded Rings
Summary :
This paper presents a genetic algorithm for designing at minimum cost a two-connected network topology such that the shortest cycle (referred to as a ring) to which each edge belongs does not exceed a given maximum number of hops. The genetic algorithm introduces a solution representation in which constraints such as connectivity and ring constraints are easily encoded. Furthermore, a problem specific crossover operator that ensures solutions generated through genetic evolution are all feasible is also proposed. Hence, both checking of the constraints and repair mechanism can be avoided thus resulting in increased efficiency. Experimental evaluation shows the effectiveness of the proposed GA.
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- IEICE TRANSACTIONS on Fundamentals Vol.E84-A No.6 pp.1545-1548
- Publication Date
- 2001/06/01
- Publicized
- Online ISSN
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- Type of Manuscript
- Special Section LETTER (Special Section on Papers Selected from 2000 International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2000))
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Beatrice M. OMBUKI, Morikazu NAKAMURA, Zensho NAKAO, Kenji ONAGA, "An Evolutionary Algorithm Approach to the Design of Minimum Cost Survivable Networks with Bounded Rings" in IEICE TRANSACTIONS on Fundamentals,
vol. E84-A, no. 6, pp. 1545-1548, June 2001, doi: .
Abstract: This paper presents a genetic algorithm for designing at minimum cost a two-connected network topology such that the shortest cycle (referred to as a ring) to which each edge belongs does not exceed a given maximum number of hops. The genetic algorithm introduces a solution representation in which constraints such as connectivity and ring constraints are easily encoded. Furthermore, a problem specific crossover operator that ensures solutions generated through genetic evolution are all feasible is also proposed. Hence, both checking of the constraints and repair mechanism can be avoided thus resulting in increased efficiency. Experimental evaluation shows the effectiveness of the proposed GA.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e84-a_6_1545/_p
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@ARTICLE{e84-a_6_1545,
author={Beatrice M. OMBUKI, Morikazu NAKAMURA, Zensho NAKAO, Kenji ONAGA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Evolutionary Algorithm Approach to the Design of Minimum Cost Survivable Networks with Bounded Rings},
year={2001},
volume={E84-A},
number={6},
pages={1545-1548},
abstract={This paper presents a genetic algorithm for designing at minimum cost a two-connected network topology such that the shortest cycle (referred to as a ring) to which each edge belongs does not exceed a given maximum number of hops. The genetic algorithm introduces a solution representation in which constraints such as connectivity and ring constraints are easily encoded. Furthermore, a problem specific crossover operator that ensures solutions generated through genetic evolution are all feasible is also proposed. Hence, both checking of the constraints and repair mechanism can be avoided thus resulting in increased efficiency. Experimental evaluation shows the effectiveness of the proposed GA.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - An Evolutionary Algorithm Approach to the Design of Minimum Cost Survivable Networks with Bounded Rings
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1545
EP - 1548
AU - Beatrice M. OMBUKI
AU - Morikazu NAKAMURA
AU - Zensho NAKAO
AU - Kenji ONAGA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E84-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2001
AB - This paper presents a genetic algorithm for designing at minimum cost a two-connected network topology such that the shortest cycle (referred to as a ring) to which each edge belongs does not exceed a given maximum number of hops. The genetic algorithm introduces a solution representation in which constraints such as connectivity and ring constraints are easily encoded. Furthermore, a problem specific crossover operator that ensures solutions generated through genetic evolution are all feasible is also proposed. Hence, both checking of the constraints and repair mechanism can be avoided thus resulting in increased efficiency. Experimental evaluation shows the effectiveness of the proposed GA.
ER -
English
