  The Clustered Traveling Salesman Problem (CTSP) is a variant of the popular
Traveling Salesman Problem (TSP) arising from a number of real-life
applications. In this work, we explore a transformation approach that solves
the CTSP by converting it to the well-studied TSP. For this purpose, we first
investigate a technique to convert a CTSP instance to a TSP and then apply
powerful TSP solvers (including exact and heuristic solvers) to solve the
resulting TSP instance. We want to answer the following questions: How do
state-of-the-art TSP solvers perform on clustered instances converted from the
CTSP? Do state-of-the-art TSP solvers compete well with the best performing
methods specifically designed for the CTSP? For this purpose, we present
intensive computational experiments on various benchmark instances to draw
conclusions.
