In combat operations, it is very common to have difficulties in the rational scheduling of multi-task and multi-support resources. In this paper, a mathematical model is constructed with the objective function of the shortest total time of task completion, and the global optimal solution of support resource scheduling is obtained by using genetic algorithm for iterative optimization. The genetic algorithm is improved by self-adaptation, the operation of emigration and crossover, and the optimization of iterative conditions, which solves the problem that the global optimal solution can not be obtained by premature convergence, and improves the efficiency of the algorithm by 76. 4%. The simulation results show that the method is feasible, and it can quickly and accurately complete a variety of support resource scheduling and form a task allocation scheme to meet the realistic requirements of combat force resource support at this stage. The research results have good application value and development prospects, which can efficiently complete the support resource scheduling without generating redundant burden.