Metaheuristic algorithms are being used extensively in the optimization of the planning, scheduling, and operation of electrical networks. Multiple studies carried out in the literature have shown that the performance of these methods depends on the particularities of the problem and the initial setup of the algorithm. This paper is testing the performance of two recent metaheuristic algorithms, the Tiki Taka Algorithm (TTA) and Archimedes optimization Algorithm (AOA), against the older Particle Swarm optimization (PSO), in solving the problem of optimal Distributed Generation (DG) placement in electricity distribution networks (EDN). A comparative case study highlights the particularities of each algorithm.