The EA is a powerful tool for
solving highly complex and/or non- linear computationally intensive
problems. Because the success of this programming tool is based
on testing the fitness of a solution in a simulated environment,
it is capable of optimizing for a wide variety of variables
simultaneously. The variables need not have a linear
relationship to one another for this technique to be successful,
in fact the more complex the solution space, the better the EA
performs compared to other optimization tools.
While the EA is excellent at attaining a very good solution, in some cases this solution may not be the global
optimum. Sometimes it falls into a local "valley" in the solution set and is unable to climb
out of the local minimum to find the optimum. In most cases, however, it is possible for the EA to arrive at
the global optimum and much work is being done to ensure that the EA does arrive at this
optimum.
The EA, and its cousin the Genetic Algorithm
(GA), have been used in wide ranging computational disciplines
with sometimes amazing results. The main thing holding this
computational approach back may be that researchers have assumed many
classes of problems were unsolvable due to the intense
computational resources needed, and are unaware that an approach
is available that can sidestep this issue.
Most EAs work like mad in the background
and then provide one final result, and the researcher assumes
great things are going on during the computation. The Visual EA
was designed to provide something to see
as the algorithm works. The Basic Demo
allows the user observe the progress as the best-solution-so-far is
displayed for you.
The program has been converted from C to Java. The speed suffers, but
it is something that can be viewed on a web page. The demo applet
must be viewed with a Java compatible browser running
on a multi- threaded operating system. (eg: Netscape 3.0 on
Windows 95.)
There are 3 things under your control with the Basic Demo:
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