Abstract Gravitational Search Algorithm (GSA) is an optimization method inspired by the
theory of Newtonian gravity in physics. Till now, many variants of GSA have been …

Today, many metaheuristics algorithms have been developed are inspired by the physical
phenomena or behaviors of natural creatures that are very effective in solving complex …

Theoretical analysis of swarm intelligence and evolutionary algorithms is relatively less
explored area of research. Stability and convergence analysis of swarm intelligence and …

Gravitational search algorithm (GSA), a recent meta-heuristic algorithm inspired by Newton's
law of gravity and mass interactions, shows good performance in various optimization …

A reliable nuclei segmentation is still an open-ended problem, especially in the breast
cancer histology images. For the same, this paper proposes an intelligent gravitational …

Particle swarm optimization (PSO) is one of the most efficient and popular swarm
intelligence-based search algorithms for continuous optimization. PSO provides the …

The identification of real-world plants and processes, which are nonlinear in nature,
represents a challenging problem. Currently, the Hammerstein model is one of the most …

This paper proposes an easily understandable Grey Wolf Optimizer (GWO) applied to the
optimal tuning of the parameters of Takagi-Sugeno proportional-integral fuzzy controllers …

Abstract The Artificial Electric Field Algorithm (AEFA) is a recently developed optimization
algorithm inspired by the principles of electrostatic force and the law of motion. It operates as …

In this paper, a new hybrid algorithm based on moth–flame optimization (MFO) and teaching–
learning-based optimization (TLBO) algorithm named as MFO–TLBO is proposed to …