This　paper　describes　a　dynamic　convexized　method　for　solving　the　symmetric　traveling　salesman　problem　(TSP).　We　construct　an　auxiliary　function　and　design　an　algorithm　based　on　this　function.　The　possibility　of　sinking　into　a　previous　local　minimizer　can　be　reduced　by　adjusting　the　value　of　the　parameter　in　the　auxiliary　function.　We　have　verified　the　correctness　of　this　approach　both　in　theory　and　experiment.　Computational　tests　show　that　the　algorithm　is　effective.　©2010　IEEE.