Abstract The Mountain Gazelle Optimizer (MGO), a novel meta-heuristic algorithm inspired
by the social life and hierarchy of wild mountain gazelles, is suggested in this paper. In this …

Mathematical programming and meta-heuristics are two types of optimization methods. Meta-
heuristic algorithms can identify optimal/near-optimal solutions by mimicking natural …

A new nature-inspired optimization method, named the Golden Jackal Optimization (GJO)
algorithm is proposed, which aims to provide an alternative optimization method for solving …

This paper presents a novel bio-inspired algorithm inspired by starlings' behaviors during
their stunning murmuration named starling murmuration optimizer (SMO) to solve complex …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

Dandelion Optimizer (DO) is a recently proposed swarm intelligence algorithm that
coincides with the process of finding the best reproduction site for dandelion seeds …

Particle swarm optimization (PSO) is one of the most famous swarm-based optimization
techniques inspired by nature. Due to its properties of flexibility and easy implementation …

This work presents a novel nature-inspired metaheuristic called Nutcracker Optimization
Algorithm (NOA) inspired by Clark's nutcrackers. The nutcrackers exhibit two distinct …

Over the past years, many efforts have been accomplished to achieve fast and accurate
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …

In this paper, a new stochastic optimization algorithm is introduced, called Driving Training-
Based Optimization (DTBO), which mimics the human activity of driving training. The …