title: Landscape encodings enhance optimization.
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.
authors.affiliation: Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany. klemm@bioinf.uni-leipzig.de
authors.forename: Konstantin
authors.initials: K
authors.lastname: Klemm
authors.forename: Anita
authors.initials: A
authors.lastname: Mehta
authors.forename: Peter F
authors.initials: PF
authors.lastname: Stadler
mesh_terms: D019143:Evolution, Molecular; D008957:Models, Genetic