Optimize the allocation of community continuing education resources to improve the community humanistic environment. This paper counts the amount of community continuing education resources, analyzes the efficiency objective and equity objective of resource allocation. And design the continuing education resource system based on optimization algorithm. Select the genetic algorithm as the optimal configuration scheme solving algorithm, use the genetic principle to be configured resources to solve the unknown real number form coding. Find the optimal solution of the configuration scheme through the process of generating the initial population and defining the fitness function. Integrate adaptive mutation and small habitat technology to improve the genetic algorithm and improve the performance of the algorithm. The results show that the improved genetic algorithm achieves the convergence of the objective function value at 90 iterations. The convergence time of the algorithm is no more than 1500s in all three community resource allocation solutions. The results of the five characteristic indexes are high, high, low, high, and high, respectively. The average configuration cost is only 78.215*103 yuan, which is lower than the comparison algorithm, and it has performance advantages such as fast convergence speed and low solution cost.
