Global　routing　is　an　important　link　in　very　large　scale　integration　(VLSI)　design.　As　the　best　model　of　global　routing,　X-architecture　Steiner　minimal　tree　(XSMT)　has　a　good　performance　in　wire　length　optimization.　XSMT　belongs　to　non-Manhattan　structural　model,　and　its　construction　process　cannot　be　completed　in　polynomial　time,　so　the　generation　of　XSMT　is　an　NP　hard　problem.　In　this　paper,　an　X-architecture　Steiner　minimal　tree　algorithm　based　on　multi-strategy　optimization　discrete　differential　evolution　(XSMT-MoDDE)　is　proposed.　Firstly,　an　effective　encoding　strategy,　a　fitness　function　of　XSMT,　and　an　initialization　strategy　of　population　are　proposed　to　record　the　structure　of　XSMT,　evaluate　the　cost　of　XSMT　and　obtain　better　initial　particles,　respectively.　Secondly,　elite　selection　and　cloning　strategy,　multiple　mutation　strategies,　and　adaptive　learning　factor　strategy　are　presented　to　improve　the　search　process　of　discrete　differential　evolution　algorithm.　Thirdly,　an　effective　refining　strategy　is　proposed　to　further　improve　the　quality　of　the　final　Steiner　tree.　Finally,　the　results　of　the　comparative　experiments　prove　that　XSMT-MoDDE　can　get　the　shortest　wire　length　so　far,　and　achieve　a　better　optimization　degree　in　the　larger-scale　problem.