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Marcel Kronfeld
2007-12-11 16:38:11 +00:00
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<html>
<head>
<title>MAES - Median Selection </title>
</head>
<body>
<EFBFBD>
<h1 align="center">MAES Median Selection Strategy</h1>
<center>
</center><br>
The main application field of the Median Selection Strategy
operator are steady state algorithms.
A standard steady-state ES is equivalent to a (mu + 1) ES.
Only one individual is generated and evaluated
at each step and gets immediately integrated into the population.
Compared to generation based algorithms the information of
new evaluated individuals can be integrated directly into the optimization process.
The idea is to approximate the selection mechanism
of a standard (mu,lambda) ES, by
using a fitness buffer containing
fitness values of the last n evaluations.
Given a relative rate of acceptance r=mu\lambda.
A newly evaluated individual substitutes the worst individual
of the population, if it has a better fitness than the r*n best individuals
in the buffer.
<ul>
<li>The problem to be solved.</li>
<li>A seed value for the random number genarator.</li>
<li>A termination criterium for the algorithm.</li>
<li>The used population.</li>
</ul>
</body>
</html>