“…About 35% of the reviewed studies worked on an update to swarm intelligence optimization algorithms [ 40 , 44 , 46 ] such as particle swarm optimization (PSO) [ 42 , 58 , 66 , 68 , 69 , 74 , 75 , 76 , 77 , 81 , 88 , 97 , 99 ], ant colony optimization (ACO) [ 33 ], and bee colony optimization (BCO) [ 48 , 65 ], due to their ability to solve complex problems and provide a satisfactory solution in a feasible time [ 90 ]. These algorithms are applied to enhance network performance by combining them with other approaches and then comparing the obtained results with other algorithms, such as the genetic, greedy, and multi-objective evolutionary algorithms.…”