Systems and Control
Broad in scope, this text shows the multidisciplinary role of dynamics and control, presents neural networks, fuzzy systems, and genetic algorithms, and provides a self-contained introduction to chaotic systems.
TABLE OF CONTENTS Systems and Control
Chapter 10: Genetic and Evolutionary Algorithms
The word "algorithm" itself is quite interesting; at first glance it may look as though someone intended to write "logarithm" but jumbled up the first four letters. The word did not appear in Webster's New World Dictionary as late as 1957; we find only the older form "algorism" with its ancient meaning, i.e., the process of doing arithmetic using Arabic numerals. " " Finally, historians of mathematics found the true origin of the word algorism: it comes from the name of a famous Persian textbook author, Abu Ja'far Mohammed ibn M s al-Khow rizm (c. 825) Al-Khow rizm wrote the celebrated book Kitab al jabr w'al-muqabala ("Rules of restoration and reduction") The modern meaning for algorithm is quite similar to that of recipe, process, method, technique, procedure, routine, except that the word "algorithm" connotes something just a littldifferent.
The Art of Computer Programming, Volume I [162, pp. 1 3]
Overview
Genetic algorithms, introduced by Holland [124] in the 1960s, have been originally proposed to model adaptive processes, both natural and man-made. In this chapter we discuss applications of genetic algorithms to solving optimization problems. Genetic algorithms were inspired by biological genetics and evolutionary processes. This is the reason for biological terms being used in the context of genetic algorithms. One of the variants of genetic algorithms, called the evolutionary algorithm, is also presented.
10.1 Genetics as an Inspiration for an Optimization Approach
The gene is the basic unit of inheritance. Genes are pieces of...
Copyright Oxford University Press, Inc. 2003 under license agreement with Books24x7
