ABSTRACT
Associate Professor, Department of Electrical and Computer Engineering, Concordia University, Montreal, Canada
Evolutionary computation, in all of its flavors (genetic algorithms [GA], genetic programming [GP], evolutionary strategies [ES], and evolutionary programming [EP]), offers an attractive paradigm for the optimization of and, to a lesser degree, design of scientific and engineering artifacts. They offer the practitioner the opportunity to utilize artificial evolution rather than human intuition as a tool for searching unknown or partially characterized spaces of high dimensionality for the purpose of identifying optimal or acceptable solutions to well-defined problems.
