This　paper　proposed　a　hybrid　approach　of　Genetic　Algorithm　(GA)　and　Ant　Colony　Optimization　(ACO)　for　the　Traveling　Salesman　Problem.　In　this　approach,　every　chromosome　of　GA　is　at　the　same　time　an　ant　of　ACO.　Whenever　GA　performs　the　operation　of　crossover　and　mutation,　the　approach　firstly　computes　the　linkage　strength　between　gene　codes　of　parental　chromosome(s)　according　to　the　pheromone　matrix　of　ACO,　and　it　then　selects　the　crossover　or　mutation　point(s)　according　to　the　linkage　strength.　A　threshold　is　generated　to　classify　the　gene　linkage　as　strong　or　weak,　the　strong　linkage　segments　of　parents　are　retained　to　offspring　as　far　as　possible.　By　this　way,　GA　can　avoid　its　useful　building　blocks　being　frequently　destroyed　by　genetic　operations.　Experiments　on　TSPLIB　validated　the　building　block　learning　capability　of　our　approach.