Structural　progressive　collapse　design　is　essential　for　improving　the　robustness　of　structures　against　accidental　local　loads.　In　this　study,　a　design　framework　was　developed　for　optimizing　the　nonlinear　dynamic　progressive　collapse　design　of　reinforced　concrete　(RC)　frame　structures.　An　objective　function　featuring　both　structural　response　and　material　consumption　was　combined　with　a　cluster　computing　technology　and　the　global　opti-mization　algorithm　to　optimize　a　structure　for　resisting　progressive　collapse.　A　four-story　RC　frame　was　taken　as　an　example.　The　design　framework　was　adopted　to　achieve　precise　control　of　its　structural　progressive　collapse　response　with　optimization　of　the　material　consumption　to　the　maximum　extent.　The　design　outcomes　of　global　and　sequential　design　schemes,　including　structural　resistance　and　material　consumption,　were　compared　to　devise　the　best　optimized　progressive　collapse　design　strategy.　This　research　can　serve　as　a　reference　for　the　development　of　efficient　and　accurate　structural　progressive　collapse　design　methods.