32 lines
1.1 KiB
HTML
32 lines
1.1 KiB
HTML
<html>
|
||
<head>
|
||
<title>MAES - Median Selection </title>
|
||
</head>
|
||
<body>
|
||
|
||
<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> |