Landscape encoding: faster optimization in larger spaces
Konstantin Klemm, Anita Mehta, Peter Florian Stadler, Supratik Bose · arXiv (Cornell University) · 2011
Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe NM 87501, USA(Dated: April 28, 2011)Hard combinatorial optimisation problems deal with the search for the ground state of discretesystems under strong frustration such as spin glasses. A transformation of state variables mayenhance computational tractability. It has been argued that these state encodings are to be choseninvertible to retain the original size of the state space. Here we show how redundant non-invertibleencodings enhance optimisation by enriching the density of low-energy states. In addition, smoothlandscapes may be established on encoded state spaces to guide local search dynamics towards theground state.