Hyper-heuristics have emerged as a way to raise the level of generality of search techniques
for computational search problems. This is in contrast to many approaches, which represent …

Over the last few years, coarse-grained molecular dynamics has emerged as a way to model
large and complex systems in an efficient and inexpensive manner due to its lowered …

Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

This paper proposes a new population-based optimization algorithm called hunter–prey
optimizer (HPO). This algorithm is inspired by the behavior of predator animals such as …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

Accurate estimation of critical parameters of the photovoltaic models is a highly demanding
task in modeling and simulating the photovoltaic systems. In this research, a diversification …

This paper proposes a novel population-based optimization algorithm called Sine Cosine
Algorithm (SCA) for solving optimization problems. The SCA creates multiple initial random …

Abstract The Sine Cosine Algorithm (SCA) has received much attention from engineering
and scientific fields since it was proposed. Nevertheless, when solving multimodal or …

In this paper, we propose enhancements to Beetle Antennae search (BAS) algorithm, called
BAS-ADAM, to smoothen the convergence behavior and avoid trapping in local-minima for a …

Optimization and decision making problems in various fields of engineering have a major
impact in this current era. Processing time and utilizing memory is very high for the currently …