As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

This review aims to exploit a study on different benchmark test functions used to evaluate the
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …

This study proposes a new metaheuristic algorithm called sand cat swarm optimization
(SCSO) which mimics the sand cat behavior that tries to survive in nature. These cats are …

Nature-inspired optimization algorithms can solve different engineering and scientific
problems owing to their easiness and flexibility. There is no need for structural modifications …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

In recent years, several multi-method and multi-operator-based algorithms have been
proposed for solving optimization problems. Generally, their performance is better than other …

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …

Electrostatic Force is one of the fundamental force of physical world. The concept of electric
field and charged particles provide us a strong theory for the working force of attraction or …

Particle swarm optimization (PSO) is a population based meta-heuristic search algorithm
that has been widely applied to a variety of problems since its advent. In PSO, the inertial …

In recent years, researchers have been focused on solving optimization problems in order to
determine the global optimum. Increasing the dimension of a problem increases its …