X-architecture　Steiner　minimal　tree　(XSMT)　problem　is　an　NP-hard　problem,　and　it　is　the　best　connection　model　for　a　multi-terminal　net　in　non-Manhattan　global　routing　problem.　An　XSMT　construction　algorithm　based　on　hybrid　transformation　strategy　and　self-adapting　particle　swarm　optimization(PSO)　is　proposed.　Firstly,　an　effective　hybrid　transformation　strategy　is　designed　to　enlarge　the　search　space　and　enhance　the　convergence　of　the　algorithm.　Secondly,　the　crossover　and　mutation　operators　based　on　union-find　sets　and　a　self-adapting　strategy　to　adjust　the　learning　factors　are　proposed　to　satisfy　the　robustness　of　particle　coding　and　further　speed　up　the　convergence　of　algorithm.　The　experimental　results　show　that　the　proposed　algorithm　efficiently　produces　a　better　solution　than　others.　Moreover,　it　obtains　a　series　of　XSMTs　with　different　topology　but　same　length.　Thus,　it　provides　a　variety　of　options　for　global　routing　and　opportunities　to　reduce　congestion.　©　2018,　Science　Press.　All　right　reserved.