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.