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A memetic algorithm for the
generalized traveling salesman problem
Gregory Gutin, D Karapetyan and N Krasnogor
In: NICSO 2007, November 8-10, 2007, Sicily, Italy.
AbstractThe generalized traveling salesman problem (GTSP) is an extension of
the well-known traveling salesman problem. In GTSP, we are given a
partition of cities into groups and we are required to find a
minimum length tour that includes exactly one city from each group.
The aim of this paper is to present a new memetic algorithm for GTSP
which clearly outperforms the state-of-the-art memetic algorithm of
Snyder and Daskin \cite{RandomKeyGA} with respect to the quality of
solutions. Computational experiments conducted to compare the two
heuristics also show that our improvements come at a cost of longer
running times, but the running times still remain within reasonable
bounds (at most a few minutes). While the Snyder-Daskin memetic
algorithm is designed only for the Symmetric GTSP, our algorithm can
solve both symmetric and asymmetric instances. Unlike the
Snyder-Daskin heuristic, we use a simple machine learning approach
as well. [Edit]
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