The　challenges　arising　from　the　management　of　municipal　solid　waste　(MSW)　have　a　profound　impact　on　the　sustainable　development　of　urban　areas.　As　a　sustainable　solution,　the　transportation　of　MSW　underground　offers　the　potential　to　alleviate　traffic　congestion　and　reduce　environmental　pollution.　In　this　study,　we　propose　the　implementation　of　a　large-scale　underground　waste　collection　system　(UWCS).　To　begin,　a　comprehensive　operational　process　for　the　UWCS　is　designed　based　on　an　intelligent　technology　system,　including　facility　operation,　processing　workflow,　and　technical　parameters.　Additionally,　network　planning　methods　for　the　UWCS　are　presented.　A　mixed-integer　linear　programming　model　is　formulated　with　the　objective　of　minimizing　total　cost.　This　model　determines　the　optimal　location　and　allocation　of　nodes　within　the　network,　as　well　as　the　pipeline　layout　and　flow　direction.　Given　the　computational　complexity,　a　hybrid　optimization　method,　namely　the　genetic　greedy　algorithms　and　genetic　variable　neighborhood　search　algorithms　(GGA-GVNS),　is　devised　to　obtain　high-quality　solutions　for　the　model.　Finally,　to　validate　the　efficacy　of　the　proposed　method,　a　simulation　is　conducted　in　the　central　city　of　Nanjing,　China.　The　results　demonstrate　that　the　implementation　of　the　UWCS　network　in　Nanjing＇s　city　center　can　yield　an　annual　benefit　of　USD　5.99　million.　Moreover,　a　sensitivity　analysis　reveals　further　MSW　management-related　insights　and　long-term　planning　strategies.