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25 April 2024
 
  » arxiv » cond-mat/0010337

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Optimization with Extremal Dynamics
S. Boettcher ; A. G. Percus ;
Date 23 Oct 2000
Journal Phys. Rev. Lett, 86 (2001) 5211
Subject Statistical Mechanics; Optimization and Control; Neural and Evolutionary Computing | cond-mat.stat-mech cs.NE math.OC
AffiliationEmory U.) and A. G. Percus (Los Alamos
AbstractWe explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively replaces extremely undesirable variables of a single sub-optimal solution with new, random ones. Large fluctuations ensue, that efficiently explore many local optima. With only one adjustable parameter, the heuristic’s performance has proven competitive with more elaborate methods, especially near phase transitions which are believed to coincide with the hardest instances. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of +-J spin glasses in d=3 and 4.
Source arXiv, cond-mat/0010337
Other source [GID 98301] pmid11384460
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