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.
[1]
David S. Johnson,et al.
Computers and In stractability: A Guide to the Theory of NP-Completeness. W. H Freeman, San Fran
,
1979
.
[2]
I. Morgenstern,et al.
Heidelberg Colloquium on Glassy Dynamics
,
1987
.
[3]
G. G. Stokes.
"J."
,
1890,
The New Yale Book of Quotations.
[4]
John H. Holland,et al.
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
,
1992
.
[5]
R. Lathe.
Phd by thesis
,
1988,
Nature.