<p>In the pre-prevention stage, firefighting force configuration and facility layout play a critical role in reducing fire extinguishing time (FET) during the early-stage forest fire rescue. It is acknowledged that there is a scarcity of quantitative evaluation research establishing a connection between observed forest fire behaviors and pre-prevention research. Therefore, we propose a forest fire rescue framework to jointly optimize firefighting force configuration and facility layout. As an iterative optimization framework based on fire spread and suppression model (FSSM), firefighting force configuration and facility layout methods use differential-evolution-based algorithm and deep neural network to adjust the configuration funds of various firefighting forces and plan the spatial layout of multiple firefighting facilities. With iterations increasing, the proposed method can continue to find better solutions than before. Moreover, through the offensive and defensive procedures in FSSM, the best configuration and layout solution can mirror multi-rescue-resource interactions and mutual restraints. The performance of the proposed framework is validated through various maps and experiments in terms of FET, forest burned area, and uncontrolled fire rate, even under extreme wind-speed pressure conditions. This implies that the proposed framework demonstrates favorable adaptability. Furthermore, the proposed framework can be introduced into the related dynamic interactions and constraints optimization scenarios (e.g., smart factories, smart construction sites, and more), thereby opening the door of digital-twin simulation optimization.</p>