Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An improved genetic algorithm with a local optimization strategy and an
  extra mutation level for solving traveling salesman problem   The Traveling salesman problem (TSP) is proved to be NP-complete in most
cases. The genetic algorithm (GA) is one of the most useful algorithms for
solving this problem. In this paper a conventional GA is compared with an
improved hybrid GA in solving TSP. The improved or hybrid GA consist of
conventional GA and two local optimization strategies. The first strategy is
extracting all sequential groups including four cities of samples and changing
the two central cities with each other. The second local optimization strategy
is similar to an extra mutation process. In this step with a low probability a
sample is selected. In this sample two random cities are defined and the path
between these cities is reversed. The computation results show that the
proposed method also finds better paths than the conventional GA within an
acceptable computation time.

10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org