A Hybrid Genetic Algorithm to the Program Optimization Model Based on a Heterogeneous Network

Project construction and development are an important part of future army designs. In today's world, intelligent warfare and joint operations have become the dominant developments in warfare, so the construction and development of the army need top-down, top-level design, and comprehensive planning. The traditional project development model is no longer sufficient to meet the army's complex capability requirements. Projects in various fields need to be developed and coordinated to form a joint force and improve the army's combat effectiveness, At the same time, when a program consists of large-scale project data, the effectiveness of the traditional, precise mathematical planning method is greatly reduced because it is time-consuming, costly, and impractical. To solve above problems, this paper proposes a rnulti-stage program optimization model based on a heterogeneous network and hybrid genetic algorithm and verifies the effectiveness and feasibility of the model and algorithm through an example. The results show that the hybrid algorithm proposed in this paper is better than the existing meta-heuristic algorithm.