1998/05/12 by Reimer Kuehn, Yu-Cheng Lin, Kuehn, Reimer +3
Computer Science · Engineering · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Logic, programming, and type systems #Manufacturing Process and Optimization #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.dis-nn #cond-mat.stat-mech
paper · pdf · doi:10.48550/arxiv.cond-mat/9805137
16 pages, 10 eps figures
arxiv created 1998/05/12 · openalex publication_date 1998/05/12 · arxiv updated 2009/11/30 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
A new approach to combinatorial optimization based on systematic move-class deflation is proposed. The algorithm combines heuristics of genetic algorithms and simulated annealing, and is mainly entropy-driven. It is tested on two problems known to be NP hard, namely the problem of finding ground states of the SK spin--glass and of the 3-D ± J spin-glass. The algorithm is sensitive to properties of phase spaces of complex systems other than those explored by simulated annealing, and it may therefore also be used as a diagnostic instrument. Moreover, dynamic freezing transitions, which are well known to hamper the performance of simulated annealing in the large system limit are not encountered by the present setup.