Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …

The production efficiency and optimal control of wave energy converter (WEC) array are
mainly based on array layout, thus it is crucial to establish a reliable mathematical model for …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

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 …

Parameter tuning, that is, to find appropriate parameter settings (or configurations) of
algorithms so that their performance is optimized, is an important task in the development …

Abstract Grey Wolf Optimizer (GWO) algorithm is a relatively new algorithm in the field of
swarm intelligence for solving continuous optimization problems as well as real world …

SHADE is an adaptive DE which incorporates success-history based parameter adaptation
and one of the state-of-the-art DE algorithms. This paper proposes L-SHADE, which further …

Real-world optimization problems demand an efficient meta-heuristic algorithm which
maintains the diversity of solutions and properly exploits the search space of the problem to …

Social learning plays an important role in behavior learning among social animals. In
contrast to individual (asocial) learning, social learning has the advantage of allowing …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …