As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

Research in metaheuristics for global optimization problems are currently experiencing an
overload of wide range of available metaheuristic-based solution approaches. Since the …

This paper proposes a novel nature-inspired algorithm called Gaining Sharing Knowledge
based Algorithm (GSK) for solving optimization problems over continuous space. The GSK …

In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

The firefly algorithm has become an increasingly important tool of Swarm Intelligence that
has been applied in almost all areas of optimization, as well as engineering practice. Many …

Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of new
algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based …

Nowadays, it has become a necessity for operational and reliable operation of networks due
to our increased dependency over the network services. However, intruders are …

Since most metaheuristic algorithms for continuous search space have been developed, a
number of transfer functions have been proposed including S-shaped, V-shaped, linear, U …

In the field of image processing, there are several problems where the efficient search has to
be performed in complex search domain to find an optimal solution. Image enhancement …