Improvement and Application of Moth Extinguishing Algorithm in Complex Resource Scheduling Scenarios

In order to solve the problem of emergency resource scheduling in complex scenarios with multiple natural disasters, this paper proposes an improved algorithm based on double adaptive factors (DAI-MFO), which effectively improves the model optimization and algorithm optimization performance of MFO and LMFO. Firstly, variable normalization and constraint conditions are introduced as penalty terms, and the applicability of the model is improved by population initialization technology. Secondly, the adaptive weight factor is added to improve the initial global search ability. Avoid falling into local optimal problems; Finally, the adaptive speed factor is added to accelerate the convergence rate in the late iteration. In order to improve the convergence speed, and then obtain better global optimal solution development ability.