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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/530

Title: Landscape Encodings Enhance Optimization
Authors: Klemm, Konstantin
Mehta, Anita
Stadler, Peter F
Issue Date: 2012
Publisher: PLoS ONE
Citation: Konstantin Klemm, Anita Mehta and Peter F. Stadler, Landscape encodings enhance optimization, PLoS ONE, 2012, 7(4), e34780.
Abstract: Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non- invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state.
URI: http://hdl.handle.net/123456789/530
Appears in Collections:2012

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