In the realm of cloud computing, effective resource utilization and load balancing (LB) are paramount for enhancing system performance and optimizing resource allocation. This paper presents a novel LB technique for cloud computing, combining Genetic Algorithm (GA), Simulated Annealing (SA), and Particle Swarm Optimization (PSO). The advantage of this hybrid algorithm lies in its ability to leverage the strengths of each algorithm, resulting in a more efficient optimization process. The CloudSim experimental results prove that the above approach performed better in terms of execution time and makespan time as compared to GA, PSO, and hybrid GA+PSO algorithms.