Fabian Becker
b1553f3088
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36 lines
1.5 KiB
HTML
36 lines
1.5 KiB
HTML
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<title>Ackley's function</title>
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</head>
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<body>
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<h1 align="center">Ackley's function</h1>
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<center>
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<img src="images/ackleytex.jpg" width="500" height="58" aling="center">
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</center>
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<p>
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Ackley's function is multimodal and symmetrical. It is based on an exponential function and modulated by a cosine function.
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The outside region is almost planar as to the growing influence of the exponential function.
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In the center there is a steep hole as to the influence of the cosine function.<br>
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Its minimum is at: <i>f(x)</i>=<i>f</i>([0, 0, ... , 0])=0.
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<p>
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The difficulty for an optimization algorithm is mid-graded because a simple optimization-algorithm like <i>hill-climbing</i> would get stuck in a local minimum. The optimization algorithm has to search a broader environ to overcome the local minimum and get closer to the global optima.
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<p>
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<img src="images/ackley.jpg" width="480" height="360" border="2" align="center">
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<br>
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Ackley's function within the co-domain -20 >= <i>x</i> >= 20, <i>a</i>=20, <i>b</i>=0.2, <i>c</i>=2*π, <i>n</i>=2.
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<p>
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<img src="images/ackleyopt.jpg" width="480" height="360" border="2" align="center">
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<br>
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Ackley's function close to the optimum.
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<hr>
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More information about Ackley's function can be found at:
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<p>
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David. H. Ackley. <i>A connection machine for genetic hillclimbing.</i> Kluwer Academic Publishers, Boston, 1987.
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<p>
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Thomas Baeck. <i>Evolutionary Algorithms in Theory and Practice.</i> Oxford University Press, 1996.
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</body>
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</html> |