“…Luckily, meta-heuristic algorithms have recently demonstrated themselves to be highly affordable and the most trusted computing method to deal with optimization problems, including OPF problems. For instant, different meta-heuristic algorithms have been applied to solve the OPF problems such as backtracking search algorithm (BSA) [1], genetic algorithm (GA) [2], Harris Hawks optimization (HHO) [3], [4], grey wolf optimizer algorithm (GWOA) [5], AMTPG-Jaya algorithm [6], differential evolution (DE) [7], [8], effective Cuckoo search algorithm (ECSA) [9], particle swarm optimization (PSO) [10], Gorilla troops algorithm (GTA) [11], modified coyote optimization algorithm (MCSA) [12], black hole optimization (BHO) [13], the hybrid method of Cuckoo search algorithm (MCOA) and sunflower optimization (SFO) [14], improved multi-objective multi-verse algorithm (IMOMVA) [15], firefly krill herd algorithm (FHHA) [16], improved moth-flame optimization (IMFO) [17], antlion optimization (ALO) and its improved version [18], [19], marine predator algorithm (MPA) [20], social spider algorithm (SSA) [21], slime mould algorithm (SMA) [22], whale optimization algorithm (WOA) [23], and golden ratio optimization (GRO) [24]. The effectiveness of meta-heuristic algorithms has shown a huge leap forward when compared with conventional computing methods, such as the Newton-Raphson technique [25], in terms of time response, robustness, and precision degree of the final results.…”