This　paper　investigates　the　optimal　routing　design　problem　of　a　community　shuttle　system　feeding　to　metro　stations　based　on　demand-responsive　service.　The　solution　aims　to　jointly　optimize　a　set　of　customized　routes　and　the　departure　time　of　each　route　to　provide　a　flexible　shuttle　service.　Considering　a　set　of　on-demand　trip　requests　between　bus　stops　and　metro　stations,　a　mixed-integer　optimization　model　is　formulated　to　minimize　the　total　system　cost,　including　the　operation　cost　and　passenger＇s　in-vehicle　cost,　subject　to　the　constraints　on　the　route　length,　time　window,　detours,　and　vehicle　capacity.　To　solve　the　problem,　two　metaheuristic　algorithms,　i.e.　a　tabu　search　(TS)　and　a　variable　neighborhood　search　(VNS),　with　different　internal　operators　are　specifically　designed.　A　case　study　based　on　a　realistic　network　is　conducted　to　test　the　model　and　the　solution,　and　comparisons　of　the　performance　of　different　algorithms　are　investigated.