The　underlying　models　of　many　practical　problems　in　various　engineering　fields　are　equivalent　to　the　Steiner　tree　problem　in　graphs,　which　is　a　typical　NP-hard　combinatorial　optimization　problem.　Thus,　developing　a　fast　and　effective　heuristic　for　the　Steiner　tree　problem　in　graphs　is　of　universal　significance.　By　analyzing　the　advantages　and　disadvantages　of　the　fast　classic　heuristics,　we　find　that　the　shortest　paths　and　Steiner　points　play　important　roles　in　solving　the　Steiner　tree　problem　in　graphs.　Based　on　the　analyses,　we　propose　a　Steiner　point　candidate-based　heuristic　algorithm　framework　(SPCF)　for　solving　the　Steiner　tree　problem　in　graphs.　SPCF　consists　of　four　stages:　marking　SPCI　points,　constructing　the　Steiner　tree,　eliminating　the　detour　paths,　and　SPCII-based　refining　stage.　For　each　procedure　of　SPCF,　we　present　several　alternative　strategies　to　make　the　trade-off　between　the　effectiveness　and　efficiency　of　the　algorithm.　By　finding　the　shortest　path　clusters　between　vertex　sets,　several　methods　are　proposed　to　mark　the　first　type　of　Steiner　point　candidates　SPCI.　The　solution　qualities　of　the　classic　heuristics　are　effectively　improved　by　looking　SPCI　points　as　terminals.　By　constructing　a　Voronoi　diagram,　a　series　of　methods　are　suggested　to　mark　the　second　type　of　Steiner　point　candidates　SPCII.　The　feasible　solution　quality　is　efficiently　improved　by　employing　the　SPCII　points　as　the　insertable　key-vertices　in　key-vertex　insertion　local　search　method.　Numerical　experiments　show　that　the　proposed　strategies　are　all　effective　for　improving　the　solution　quality.　Compared　with　other　effective　algorithms,　the　proposed　algorithms　can　achieve　better　solution　quality　and　speed　performance.　©　The　Author(s)　2016.