In the past two decades, artificial intelligence algorithms have proved to be promising tools
for solving a multitude of tough scientific problems. Their success is due, in part, to the
elegant manner in which they avoid the sort of handicaps that often plague mathematical
programming-based tools, such as smooth and continuous objective functions. Thus,
globally optimal (or close approximations of) design can be achievable with a finite and
reasonable number of search iterations. One of the most exciting of these methods is …