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Evolving greenfield passive optical networks

Evolving greenfield passive optical networks
Evolving greenfield passive optical networks
We investigate applying an evolutionary algorithm (EA) to the design of a passive optical network (PON). We use three techniques to improve the performance. Firstly, to reduce the risk of sub-optimal convergence, we use a novel genetic encoding. Secondly, we combine the EA with a heuristic to guide the optimisation. Thirdly, we investigate various ways of sub-dividing the problem. We briefly present experiments to demonstrate how the EA performs. The results show the strengths and weaknesses of the various techniques we employ.
44-49
Bonsma, E.
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Karunatillake, N. C.
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Shipman, R.
306a968b-ea9f-4ffe-8f6e-7dc214143a31
Shackleton, M.
93f0bd00-dd65-445b-a6ca-1190bd771078
Mortimore, D.
649cf4a9-c979-4cc1-b00d-a529e71d1df1
Thompson,, Simon
4ca5ef3a-89c8-4f2b-a4e9-b654bc83587f
Nauck, Detlef
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Cui, Zhan
e6a8e8e3-aebf-4165-ba46-8b9f15575e5b
Ghanea-Hercock, Robert
71f92050-ef52-48ca-b514-d657cffc9292
Bonsma, E.
817172a4-8b33-4d5b-96d6-65f32d7d7c6a
Karunatillake, N. C.
51c10e8e-fbac-4b2a-acb5-d881559113b6
Shipman, R.
306a968b-ea9f-4ffe-8f6e-7dc214143a31
Shackleton, M.
93f0bd00-dd65-445b-a6ca-1190bd771078
Mortimore, D.
649cf4a9-c979-4cc1-b00d-a529e71d1df1
Thompson,, Simon
4ca5ef3a-89c8-4f2b-a4e9-b654bc83587f
Nauck, Detlef
819b490e-5027-42c4-b111-324722052902
Cui, Zhan
e6a8e8e3-aebf-4165-ba46-8b9f15575e5b
Ghanea-Hercock, Robert
71f92050-ef52-48ca-b514-d657cffc9292

Bonsma, E., Karunatillake, N. C., Shipman, R., Shackleton, M. and Mortimore, D. , Thompson,, Simon, Nauck, Detlef, Cui, Zhan and Ghanea-Hercock, Robert (eds.) (2003) Evolving greenfield passive optical networks. BT Technology Journal, 21 (4), 44-49.

Record type: Article

Abstract

We investigate applying an evolutionary algorithm (EA) to the design of a passive optical network (PON). We use three techniques to improve the performance. Firstly, to reduce the risk of sub-optimal convergence, we use a novel genetic encoding. Secondly, we combine the EA with a heuristic to guide the optimisation. Thirdly, we investigate various ways of sub-dividing the problem. We briefly present experiments to demonstrate how the EA performs. The results show the strengths and weaknesses of the various techniques we employ.

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Published date: October 2003
Organisations: Electronics & Computer Science

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Local EPrints ID: 259499
URI: https://eprints.soton.ac.uk/id/eprint/259499
PURE UUID: 98fd061d-d0eb-4804-8d7e-94097a72109a

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Date deposited: 30 Jun 2004
Last modified: 19 Jul 2019 22:40

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