Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: gBeam-ACO: a greedy and faster variant of Beam-ACO   Beam-ACO, a modification of the traditional Ant Colony Optimization (ACO)
algorithms that incorporates a modified beam search, is one of the most
effective ACO algorithms for solving the Traveling Salesman Problem (TSP).
Although adding beam search to the ACO heuristic search process is effective,
it also increases the amount of work (in terms of partial paths) done by the
algorithm at each step. In this work, we introduce a greedy variant of Beam-ACO
that uses a greedy path selection heuristic. The exploitation of the greedy
path selection is offset by the exploration required in maintaining the beam of
paths. This approach has the added benefit of avoiding costly calls to a random
number generator and reduces the algorithms internal state, making it simpler
to parallelize. Our experiments demonstrate that not only is our greedy
Beam-ACO (gBeam-ACO) faster than traditional Beam-ACO, in some cases by an
order of magnitude, but it does not sacrifice quality of the found solution,
especially on large TSP instances. We also found that our greedy algorithm,
which we refer to as gBeam-ACO, was less dependent on hyperparameter settings.

30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an