Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous
optimization. For these reasons DE has often been employed for solving various …

Since different features may require different costs, the cost-sensitive feature selection
problem become more and more important in real-world applications. Generally, it includes …

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 …

Surrogate assisted global optimization is gaining popularity. Similarly, modern advances in
computing power increasingly rely on parallelization rather than faster processors. This …

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

Recent advances in the information and communication technologies are leading to an
exponential growth in the amount of data stored in databases. It has been estimated that this …

The growth and development of scientific applications have demanded the creation of
efficient resource management systems. Resource provisioning and scheduling are two …

Thanks to their inherent properties, probabilistic graphical models are one of the prime
candidates for machine learning and decision making tasks especially in uncertain domains …

A fast adaptive memetic algorithm (FAMA) is proposed which is used to design the optimal
control system for a permanent-magnet synchronous motor. The FAMA is a memetic …