Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

The teaching-learning-based optimization (TLBO) algorithm is finding a large number of
applications in different fields of engineering and science since its introduction in 2011. The …

In this paper, we propose a new metaheuristic algorithm based on Lévy flight called Lévy
flight distribution (LFD) for solving real optimization problems. The LFD algorithm is inspired …

This paper presents a novel bio-inspired optimization algorithm namely the Barnacles
Mating Optimizer (BMO) algorithm to solve optimization problems. The proposed algorithm …

In last 30 years, many metaheuristic algorithms have been developed to solve optimization
problems. However, most existing metaheuristic algorithms have extra control parameters …

Grey wolf optimizer (GWO) algorithm is a relatively novel population-based optimization
technique that has the advantage of less control parameters, strong global optimization …

The machine remaining useful life (RUL), the job-machine release time and the correlation
between the maintenance duration and the machine enlistment age are, in this paper …

Over past few decades, swarm intelligent algorithms based on the intelligent behaviors of
social creatures have been extensively studied and applied for all kinds of optimization …

Neural network algorithm (NNA) is one of the newest meta-heuristic algorithms, which is
inspired by biological nervous systems and artificial neural networks. Benefiting from the …

The teaching–learning-based optimization (TLBO) algorithm has been one of most popular
bio-inspired meta-heuristic algorithms due to the competitive converging speed and high …