The book provides readers with a snapshot of the state of the art in the field of
nature-inspired computing and its application in optimization. The approach is mainly
practice-oriented: each bio-inspired technique or algorithm is introduced together with one of
its possible applications. Applications cover a wide range of real-world optimization problems:
from feature selection and image enhancement to scheduling and dynamic resource management
from wireless sensor networks and wiring network diagnosis to sports training planning and gene
expression from topology control and morphological filters to nutritional meal design and
antenna array design. There are a few theoretical chapters comparing different existing
techniques exploring the advantages of nature-inspired computing over other methods and
investigating the mixing time of genetic algorithms. The book also introduces a wide range of
algorithms including the ant colony optimization the bat algorithm genetic algorithms the
collision-based optimization algorithm the flower pollination algorithm multi-agent systems
and particle swarm optimization. This timely book is intended as a practice-oriented reference
guide for students researchers and professionals.
