Multi-scale search, modular variation, and adaptive neighbourhoods
Multi-scale search, modular variation, and adaptive neighbourhoods
This paper investigates a framework for multi-scale search, which makes use of automatically defined multi-variable groupings to search over multiple scales of organisation. We show how this method redefines the variational neighbourhood visible to the search process to efficiently find high quality optima. We use a transparent two-scale modular problem to provide a clear explanation of when and how this approach works, supporting this with analysis of expected runtimes. This problem has an obvious and familiar modular structure but, unlike previous test problems used for existing model-building methods, the size of the modules are not constant but scale as a function of problem size. We show that this problem class requires multi-scale search to be solved in polynomial time.
Mills, Rob
3d53d4bc-e1de-4807-b89b-f5813f2172a7
Watson, Richard A.
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Mills, Rob
3d53d4bc-e1de-4807-b89b-f5813f2172a7
Watson, Richard A.
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Mills, Rob and Watson, Richard A.
(2011)
Multi-scale search, modular variation, and adaptive neighbourhoods.
Author's Original.
(Submitted)
Abstract
This paper investigates a framework for multi-scale search, which makes use of automatically defined multi-variable groupings to search over multiple scales of organisation. We show how this method redefines the variational neighbourhood visible to the search process to efficiently find high quality optima. We use a transparent two-scale modular problem to provide a clear explanation of when and how this approach works, supporting this with analysis of expected runtimes. This problem has an obvious and familiar modular structure but, unlike previous test problems used for existing model-building methods, the size of the modules are not constant but scale as a function of problem size. We show that this problem class requires multi-scale search to be solved in polynomial time.
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Submitted date: 2011
Organisations:
Agents, Interactions & Complexity, EEE
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Local EPrints ID: 272241
URI: http://eprints.soton.ac.uk/id/eprint/272241
PURE UUID: e8ce5371-296b-4c8b-9118-db1d75ee84dc
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Date deposited: 04 May 2011 13:49
Last modified: 01 Oct 2022 01:39
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Contributors
Author:
Rob Mills
Author:
Richard A. Watson
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