In　the　construction　process　of　construction　engineering,　there　exist　a　complex　construction　site　layout　and　multiequipment　collaborative　work.　If　a　reasonable　construction　plan　cannot　be　made　quickly　and　accurately,　the　investment　in　construction　costs　will　be　increased.　Aiming　at　the　construction　material　distribution,　this　study　proposed　a　construction　plan　planning　method　under　the　multinode　and　multivehicle　scene.　Firstly,　a　mathematical　model　of　the　material　distribution　planning　problem　in　the　multinode　multivehicle　scene　was　established.　The　basic　assumptions,　objective　functions,　and　constraints　were　proposed.　The　triangular　scalar　variables　and　＇unitization＇　processing　methods　were　incorporated　into　the　mathematical　model.　In　order　to　solve　the　problem　of　material　distribution　planning,　a　heuristic　neural　network　algorithm　was　designed.　A　＇gene-chromosome-individual＇　representation　method　and　a　＇two-step＇　calculation　concept　were　defined.　The　specific　implementation　steps　of　the　algorithm　were　given.　Fully　considering　the　type　and　quantity　of　vehicles　and　the　length　of　the　path,　a　method　of　establishing　the　mapping　relationship　between　the　construction　scheme　and　the　construction　cost　was　proposed.　The　feasibility　of　the　proposed　theoretical　method　was　verified　by　a　cable　truss　structure　model　experiment.　A　calculation　method　with　high　fitting　degree　and　fast　running　speed　was　established.　According　to　the　experiment　model,　the　best　construction　scheme　was　formed.　The　results　showed　that　the　optimal　construction　scheme　had　a　high　vehicle　loading　rate　and　a　clear　distribution　path,　which　effectively　saved　the　construction　cost　under　the　premise　of　ensuring　smooth　construction.