Optimal Communication Spanning Tree (OCST) is a well-known NP-hard problem on the graph that seeks for the spanning tree with the lowest cost. The tree cost depends on the demand and distance between each pair of nodes. This paper presents a Hybrid Genetic Algorithm (HGA) combining the basic GA with the ideas of the Particle Swarm Optimization (PSO) algorithm. In HGA, each individual exploits information of its own experience to search through the solution space with genetic operator. The experiment results show that our HGA outperforms the previous GAs with faster convergence and better solution. Categories and Subject Descriptors I.2.8 [Computing Methodologies]: Combinatorial Optimization, NP-Hard problems. General Terms Algorithms, Experimentation. Keywords Optimal Communication Spanning Tree, Genetic Algorithm.