Research on Regional Resource Optimal Allocation Based on Improved Ant Colony Algorithm

Abstract

In view of the current situation of regional resource allocation, this paper proposes a regional resource dynamic scheduling model based on the improved ant colony algorithm. This model takes the minimum cost and the least time as the optimization objectives and considers the constraint conditions such as the resource requirements and the sequence of tasks. At the same time, combined with the characteristics of the regional resource dynamic scheduling model, the traditional ant colony algorithm is improved, and an optimized encoding and decoding method is proposed. According to the results of computing power analysis, it shows that the improved ant colony algorithm has higher computational accuracy and faster convergence speed compared with the traditional ant colony algorithm.