Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Local Optima Networks: A New Model of Combinatorial Fitness Landscapes   This chapter overviews a recently introduced network-based model of
combinatorial landscapes: Local Optima Networks (LON). The model compresses the
information given by the whole search space into a smaller mathematical object
that is a graph having as vertices the local optima and as edges the possible
weighted transitions between them. Two definitions of edges have been proposed:
basin-transition and escape-edges, which capture relevant topological features
of the underlying search spaces. This network model brings a new set of metrics
to characterize the structure of combinatorial landscapes, those associated
with the science of complex networks. These metrics are described, and results
are presented of local optima network extraction and analysis for two selected
combinatorial landscapes: NK landscapes and the quadratic assignment problem.
Network features are found to correlate with and even predict the performance
of heuristic search algorithms operating on these problems.

15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con