Nowadays, a promising way to obtain hybrid metaheuristics concerns the combination of
several search algorithms with strong specialization in intensification and/or diversification …

Many strategies have been exploited for the task of feature selection, in an effort to identify
more compact and better quality feature subsets. A number of evaluation metrics have been …

Effective Butterfly Optimizer (EBO) is a self-adaptive Butterfly Optimizer which incorporates a
crossover operator in Perching and Patrolling to increase the diversity of the population. This …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

Chapter 4 GENETIC ALGORITHMS Page 1 Chapter 4 GENETIC ALGORITHMS Kumara Sastry,
David Goldberg University of Illinois, USA Graham Kendall University of Nottingham, UK 4.1 …

The term 'Memetic Algorithms'[74](MAs) was introduced in the late 80s to denote a family of
metaheuristics that have as central theme the hybridization of different algorithmic …

In the last few decades, evolutionary algorithms have emerged as a revolutionary approach
for solving search and optimization problems involving multiple conflicting objectives …

This paper proposes an effective particle swarm optimization (PSO)-based memetic
algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective …

This chapter discuss basic principles of Self-Organizing Migrating Algorithm (SOMA) that
has been firstly proposed in 1999 and published consequently in various journals, book …

Many different algorithms have been developed in the last few decades for solving complex
real-world search and optimization problems. The main focus in this research has been on …