The use of genetic algorithms has been growing exponentially since Holland published the
first papers about them. Thanks to the extraordinary increase in calculation power …

Coevolving memetic algorithms are a family of metaheuristic search algorithms in which a
rule-based representation of local search (LS) is coadapted alongside candidate solutions …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

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

Background The protein folding problem is a fundamental problems in computational
molecular biology and biochemical physics. Various optimisation methods have been …

We present an immune algorithm (IA) inspired by the clonal selection principle, which has
been designed for the protein structure prediction problem (PSP). The proposed IA employs …

This book provides a unified framework that describes how genetic learning can be used to
design pattern recognition and learning systems. It examines how a search technique, the …

In this paper we introduce a promising hybridization scheme for a Memetic Algorithm (MA).
Our MA is composed of two optimization processes, a Genetic Algorithm and a Monte Carlo …

Despite intensive studies during the last 30 years researchers are yet far from the “holy grail”
of blind structure prediction of the three dimensional native state of a protein from its …

Decomposition-based algorithms for multi-objective optimization problems have increased
in popularity in the past decade. Although convergence to the Pareto optimal front (PF) for …