In the past few decades, metaheuristics have demonstrated their suitability in addressing
complex problems over different domains. This success drives the scientific community …

In the real world, there are a number of optimization problems whose search space is
restricted to take binary values; however, there are many continuous metaheuristics with …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Genetic Algorithms are heuristic search approaches that are applicable to a wide range of
optimization problems. This flexibility makes them attractive for many optimization problems …

This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

Nature-inspired metaheuristics comprise a compelling family of optimization techniques.
These algorithms are designed with the idea of emulating some kind natural phenomena …

A History of Metaheuristics arxiv:1704.00853v1 [cs.AI] 4 Apr 2017 Page 1 A History of
Metaheuristics ∗ Kenneth Sörensen Marc Sevaux Fred Glover Abstract This chapter …

This survey compiles ideas and recommendations from more than a dozen researchers with
different backgrounds and from different institutes around the world. Promoting best practice …

For genetic algorithms (GAs) using a bit-string representation of length n, the general
recommendation is to take 1/n as mutation rate. In this work, we discuss whether this is …