Landscape encodings enhance optimization

Details Landscape encodings enhance optimization Landscape encodings enhance optimization

2011-04-26

arxiv.org/abs/1104.5024v2

PLoS One 7, e34780 (2012)

Physics

Condensed Matter

Disordered Systems and Neural Networks

8 pages, 3 figures

Scientific paper

10.1371/journal.pone.0034780

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.

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