In disaster situations, unique trip patterns distinct from regular traffic emerge, necessitating network-wide traffic control to avoid heavy congestion. Previous research lacks a realistic, rapid prediction of dynamic traffic flow during a disaster, and insufficiently considers a gradual transition sequence from traffic control in ordinary times. In this study, we developed a dynamic evacuation behavior model using the Recursive Logit model to predict evacuation departure and destination choice. Additionally, we integrated a zone-based traffic assignment model employing MFD to predict and evaluate dynamic traffic flow during disasters swiftly. Using this model, we determined the configuration of inter-zone control links to minimize congestion during evacuations. To facilitate a smooth transition from regular traffic control to optimized evacuation control, we introduced a combinatorial reconfiguration problem. We successfully devised a rapid computational solution using Zero-suppressed binary Decision Diagrams for an exhaustive search.