This　study　is　aimed　at　the　fact　that　material　allocation　and　construction　progress　cannot　be　intelligently　controlled　in　the　construction　of　prestressed　steel　structures.　An　intelligent　planning　method　of　a　material-allocation　path　for　prestressed　steel-structure　construction,　based　on　digital　twins　(DTs),　is　proposed.　Firstly,　the　characteristics　of　material　allocation　in　the　process　of　structural　construction　are　analyzed,　and　a　five-dimensional　integrated　DT　framework　for　intelligent　path-planning　is　built.　Driven　by　the　DT　framework,　the　progress　and　environmental　information　of　the　construction　site　are　collected　in　real　time.　At　the　same　time,　the　field　working　conditions　are　dynamically　simulated　in　the　virtual　model,　so　as　to　realize　the　interactive　mapping　between　physical　space　and　virtual　space.　In　each　construction　process,　by　integrating　the　progress　of　each　process　at　each　construction　location,　and　the　storage　and　allocation　of　materials,　a　multidimensional　model　for　the　intelligent　planning　of　material　allocation　is　formed.　The　information　fusion　of　virtual　and　real　space　is　carried　out　using　an　entropy　method　to　analyze　the　construction　buffer　time　and　material　allocation　time　at　each　location　of　the　construction　site.　On　this　basis,　combined　with　the　Dijkstra　algorithm,　the　transportation　time　associated　with　the　path　is　calculated　according　to　the　field　distribution　of　each　location.　A　feasibility　analysis　is　carried　out　in　the　virtual　model　and　imported　into　the　field　dynamic-marking　system.　Combined　with　radio　frequency　technology　to　guide　material　allocation　on　site,　the　intelligent　planning　of　the　material-allocation　path　is　realized.　In　this　study,　taking　the　construction　of　the　National　Speed　Skating　Pavilion　of　the　2022　Beijing　Winter　Olympics　as　an　example,　the　DT　technology　and　Dijkstra　algorithm　are　applied　to　the　intelligent　planning　of　the　material-allocation　path.　It　is　fully　verified　that　the　intelligent　method　can　effectively　coordinate　the　relationship　between　schedule　control　and　material　allocation.