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 …

This tutorial covers the canonical genetic algorithm as well as more experimental forms of
genetic algorithms, including parallel island models and parallel cellular genetic algorithms …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

Multireservoir operating policies are usually defined by rules that specify either individual
reservoir desired (target) storage volumes or desired (target) releases based on the time of …

Genetic algorithms (GAs) have become popular as a means of solving hard combinatorial
optimization problems. The first part of this chapter briefly traces their history, explains the …

Genetic algorithms (GAs) are a class of evolutionary algorithms first proposed and analyzed
by John Holland (1975). There are three features which distinguish GAs, as first proposed by …

Selection pressure can have a decisive effect on the outcome of an evolutionary search. Try
too hard, and you will end up converging prematurely, perhaps on a local maximum …

The concept of a generation gap is linked to the notion of nonoverlap** and overlap**
populations. In a nonoverlap** model parents and offspring never compete with one …

Effective map generalisation involves careful examination of the interactions between all
map symbols. These interactions may give rise to obvious graphic conflicts of proximity and …

We employ genetic algorithms, which allow for an efficient search for the global minimum of
energy landscapes, to investigate the ordered equilibrium structures formed by a binary …