An optimal power allocation is a fundamental challenge for massive multiple-input–multiple-output (MIMO) systems because the power allocation should be acclimated to time-varying channels and heavy traffic conditions throughout the communication network. Although massive model-driven algorithms have been employed to solve this issue, most of them require analytically tractable mathematical models and have a high computational complexity. This paper considers the metaheuristic algorithms for the power allocation issue. A series of state-of-the-art stochastic algorithms are compared with the benchmark algorithm on network scales. The simulation results demonstrate the superiority of the proposed algorithms against the conventional benchmark algorithms.