In this paper, a novel swarm‐based metaheuristic algorithm is proposed, which is called
tuna swarm optimization (TSO). The main inspiration for TSO is based on the cooperative …

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 …

JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in
comparison with other evolutionary optimization algorithms. However, it suffers from the …

The advent of connected devices and omnipresence of Internet have paved way for
intruders to attack networks, which leads to cyber-attack, financial loss, information theft in …

Differential evolution (DE) is one of the most popular and efficient evolutionary algorithms for
numerical optimization and it has gained much success in a series of academic benchmark …

Differential evolution (DE) is among the most efficient evolutionary algorithms (EAs) for
global optimization and now widely applied to solve diverse real-world applications. As the …

Due to the increasing complexity of optimization problems, distributed differential evolution
(DDE) has become a promising approach for global optimization. However, similar to the …

In population-based optimization algorithms (POAs), given an optimization problem, the
quality of the solutions depends heavily on the selection of algorithms, strategies and …

Niching techniques have been widely incorporated into evolutionary algorithms (EAs) for
solving multimodal optimization problems (MMOPs). However, most of the existing niching …

Seeking multiple optima simultaneously, which multimodal optimization aims at, has
attracted increasing attention but remains challenging. Taking advantage of ant colony …