In　this　paper,　we　revisit　the　long-standing　Traveling　Salesman　Problem　(TSP)　and　focus　on　the　challenging,　yet　practical　route　planning　problem　with　limited　computational　resources.　We　make　contributions　to　TSP,　one　of　the　most　famous　NP-hard　problems　by　providing　a　new　improved　approximate　solution,　which　we　term　TOpology　Preserving　Self-Organizing　Map　(TOPSOM).　TOPSOM　well　preserves　the　topology　of　the　node　map　to　be　traversed　by　maintaining　the　continuity　of　nodes　and　the　distances　between　them.　In　addition,　to　satisfy　the　requirements　of　convex　hull,　we　design　an　elastic　competitive　Hebbian　learning　rule.　TOPSOM　can　solve　large-scale　TSPs　with　high　precision　and　high　efficiency　with　limited　computational　costs.　Extensive　experimental　results　on　mainstream　route　planning　benchmarks　including　TSPLIB　and　National　TSP＇s　show　that　our　method　consistently　outperforms　baseline　methods,　by　up　to　7.7%　in　terms　of　the　Percent　Deviation　of　Mean　solution　to　best　known　solution.　©　2021　IEEE.