Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Extremal Optimization: Methods derived from Co-Evolution   We describe a general-purpose method for finding high-quality solutions to
hard optimization problems, inspired by self-organized critical models of
co-evolution such as the Bak-Sneppen model. The method, called Extremal
Optimization, successively eliminates extremely undesirable components of
sub-optimal solutions, rather than ``breeding'' better components. In contrast
to Genetic Algorithms which operate on an entire ``gene-pool'' of possible
solutions, Extremal Optimization improves on a single candidate solution by
treating each of its components as species co-evolving according to Darwinian
principles. Unlike Simulated Annealing, its non-equilibrium approach effects an
algorithm requiring few parameters to tune. With only one adjustable parameter,
its performance proves competitive with, and often superior to, more elaborate
stochastic optimization procedures. We demonstrate it here on two classic hard
optimization problems: graph partitioning and the traveling salesman problem.

19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
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The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
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The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg