📄 galib screen shots.htm
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<BODY text=#000000 bgColor=#ffffff><STRONG><A
href="http://lancet.mit.edu/ga/">GAlib</A> Screen Shots</STRONG><BR>
<P>Here are some sample screen shots of GAlib examples and of programs derived
from GAlib examples. </P>
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<TR vAlign=top>
<TD><IMG height=239 alt=ripples src="GAlib Screen Shots.files/ripples.gif"
width=338></TD>
<TD><I>Maximize a continuous function in two variables. The function looks
like ripples in a pond when drawn in three dimensions. The maximum value
is located at the center of the ripples. The example included with GAlib
shows this problem in two dimensions - the three dimensional example is a
slight modification to the GAlib example using an OpenGL widget rather
than a 2-D X drawing area. </I></TD></TR>
<TR vAlign=top>
<TD><A href="http://lancet.mit.edu/ga/images/gaview-win-657x719.gif"><IMG
height=360 alt=rings src="GAlib Screen Shots.files/gaview-win-329x360.gif"
width=329></A></TD>
<TD><I>Maximize a continuous function in two variables. Same as the
previous example, but this one is plotted in two dimensions in a simple
application built with visual c++. This version of the program lets you
change crossover, mutation, representation, algorithm, and parameters on
the fly. </I></TD></TR>
<TR vAlign=top>
<TD><IMG height=239 alt=tours src="GAlib Screen Shots.files/tours.gif"
width=338></TD>
<TD><I>This program uses a genome derived from the GAListGenome class and
solves a simple case of the travelling salesman problem. The image shows a
population of solutions, with the best solutions at the bottom left of the
window. Note that there are more than one optimal solution, and that the
deterministic crowding genetic algorithm has found more than one of these
solutions. </I></TD></TR>
<TR vAlign=top>
<TD><A href="http://lancet.mit.edu/ga/images/tspview-win-549x410.gif"><IMG
height=246 alt=tours
src="GAlib Screen Shots.files/tspview-win-329x246.gif" width=329></A></TD>
<TD><I>A windows version of the traveling salesperson problem. In this
demo you may select the type of evolution and quickly see the impact that
has on the quality and number of solutions found. </I></TD></TR>
<TR vAlign=top>
<TD><IMG height=239 alt=gantt src="GAlib Screen Shots.files/gantt.gif"
width=338></TD>
<TD><I>This program solves a class of resource-constrained scheduling
problems. It uses its own custom genome that is described in the doctoral
thesis of Matthew Wall at <CODE><A
href="http://lancet.mit.edu/~mbwall/phd">http://lancet.mit.edu/~mbwall/phd</A></CODE>
</I></TD></TR></TBODY></TABLE></BODY></HTML>
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