Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

Aerodynamic optimisation has become an indispensable component for any aerodynamic
design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind …

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 …

Although various population initialization techniques have been employed in evolutionary
algorithms (EAs), there lacks a comprehensive survey on this research topic. To fill this gap …

The evolutionary optimisation algorithms appeared as an effective alternative to
conventional statistical methods that have certain limitations in optimising complex …

As a form of evolutionary computation, particle swarm optimization is less effective in large
scale optimization since it is unable to effectively balance exploration and exploitation. To …

In the realm of modern medicine and biology, vast amounts of genetic data with high
complexity are available. However, dealing with such high-dimensional data poses …

The autonomous navigation of robots in unknown environments is a challenge since it
needs the integration of a several subsystems to implement different functionality. It needs …

In this paper, a novel swarm intelligent algorithm is proposed called ant nesting algorithm
(ANA). The algorithm is inspired by Leptothorax ants and mimics the behavior of ants …

In existing meta-heuristic algorithms, population initialization forms a huge part towards
problem optimization. These calculations can impact variety and combination to locate a …