“…9 Meta-heuristic algorithms 42,43 are computational intelligence paradigms mainly used for solving different complex optimization problems. Owing to their computational efficiency as well as superior performance in resource-constrained environments, meta-heuristic algorithms have been extensively used across the domains, including feature selection, 44 neural architecture search, 45,46 task scheduling, 47 handwritten script classification, 48 image contrast enhancement, [49][50][51] data clustering, 52 multilevel image thresholding, 53,54 and solving class imbalance problem 55,56 among others. Mostly, these algorithms are inspired from: (1) theory of evolution, such as Genetic Algorithm (GA) 57 and Differential Evolution 58 ; (2) natural behavior of organisms, such as the Whale Optimization Algorithm (WOA), 59 Cuckoo Search (CS) 60 and Flower Pollination Algorithm 61 ; (3) swarm intelligence, such as the Particle Swarm Optimization (PSO) 62 and the Grey Wolf Optimizer (GWO) 63 ; and (4) physical or scientific phenomena, such as the Gravitational Search Algorithm (GSA), 64 and the Multiverse Optimizer, 65 to name a few.…”