Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …

Many real-world problems can be reduced to combinatorial optimization on a graph, where
the subset or ordering of vertices that maximize some objective function must be found. With …

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 …

Many swarm optimization algorithms have been introduced since the early 60's,
Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms …

When solving many machine learning problems such as classification, there exists a large
number of input features. However, not all features are relevant for solving the problem, and …

Many design problems in engineering are typically multiobjective, under complex nonlinear
constraints. The algorithms needed to solve multiobjective problems can be significantly …

Engineering optimisation is typically multi-objective and multidisciplinary with complex
constraints, and the solution of such complex problems requires efficient optimisation …