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

Abstract Recently developed Harris Hawks Optimization has virtuous behavior for finding
optimum solution in search space. However, it easily get trapped into local search space for …

This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm
(EMA) to solve constrained optimization problems. The algorithm is based on the adoption of …

Abstract For many decades, Machine Learning made it possible for humans to map the
patterns that govern interpolating problems and also, provided methods to cluster and …

This paper reviews a majority of the nature-inspired algorithms, including heuristic and meta-
heuristic bio-inspired and non-bio-inspired algorithms, focusing on their source of inspiration …

This paper proposes the implementation of various metaheuristic algorithms in solving the
optimal power flow (OPF) with the presence of Flexible AC Transmission System (FACTS) …

Abstract Optimal Power Flow (OPF) is a complex and challenging problem in power system
that includes non-convex and non-linear constrained optimization problems. Due to these …

In this paper, we proposed Joint Opposite Selection (JOS) operator that is a joint of two
opposition learning techniques: the Selective Leading Opposition (SLO) and the Dynamic …

Forecasting wind power generation is crucial for ensuring grid security and the
competitiveness of the power market. This paper presents an innovative approach that …

This work proposes the implementation of recent evolutionary metaheuristic algorithm
namely, barnacles mating optimizer (BMO) to solve the Optimal Power Flow (OPF) issue …