The grasshopper optimization algorithm is one of the dominant modern meta-heuristic
optimization algorithms. It has been successfully applied to various optimization problems in …

Metaheuristic algorithms have a wide range of applications in handling optimization
problems. In this study, a new metaheuristic algorithm, called the chef-based optimization …

This paper proposes a novel nature-inspired meta-heuristic optimizer, called Reptile Search
Algorithm (RSA), motivated by the hunting behaviour of Crocodiles. Two main steps of …

To address the problem of the sparrow search algorithm (SSA) has poor global search
ability, weak local development ability, and easily falls into the local optimal solution, a multi …

Differential evolution (DE) is a powerful evolutionary algorithm (EA) for numerical
optimization. Combining with the constraint-handling techniques, recently, DE has been …

Optimization of multi-modal functions is challenging even for evolutionary and swarm-based
algorithms as it requires an efficient exploration for finding the promising region of the …

Grey wolf optimizer (GWO) is a recently developed population-based algorithm in the area of
nature-inspired optimization. The leading hunters in GWO are responsible for exploring the …

Over the recent years, continuous optimization has significantly evolved to become the
mature research field it is nowadays. Through this process, evolutionary algorithms had an …

Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired
by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has …

Metaheuristic algorithms can be summarized as a form of stochastic optimization algorithm
which does not depend on the surface gradient for optimization. These algorithms draw …