Initialisation - Revision history

Editor: /* Population cost */

2013-06-28T16:55:49Z

‎Population cost

2013-06-28T16:45:01Z

‎Basic initialisation (i0)

2013-06-28T16:44:18Z

‎Basic initialisation (i0)

2013-06-28T15:57:53Z

2013-06-28T15:46:01Z

‎Basic initialisation (i0)

2013-06-12T19:47:35Z

‎Basic APS

2013-06-11T19:05:15Z

‎Basic APS

2013-06-11T18:50:36Z

2013-06-11T18:49:42Z

‎Basic method

2013-06-11T09:18:13Z

@@ Line 11: / Line 11: @@
 === Population cost ===
-Evaluate the $N$ individuals. Save the best one as $Best$.
+Evaluate the $N$ individuals, thanks to the function $f$ we are studying. Save the best one as $Best$.
 The sum of all values (they are all supposed to be positive, which is always possible), is the initial ''population cost'' $C$. We are trying here to minimise it.

@@ Line 5: / Line 5: @@
 $N=\max\left(40+2\sqrt{D},\sqrt{40^{2}+\left(D+2\right)^{2}}\right)\label{eq:N_popsize}$
-where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+
+where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+1$.
 We will need the volume $V(0)$ of the previous simplex. As no one has been defined yet, we simply set it to 0:<br />

@@ Line 5: / Line 5: @@
 $N=\max\left(40+2\sqrt{D},\sqrt{40^{2}+\left(D+2\right)^{2}}\right)\label{eq:N_popsize}$
-where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+1$.
+where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+
-−
-Evaluate the $N$ individuals. Save the best one as $Best$.
 We will need the volume $V(0)$ of the previous simplex. As no one has been defined yet, we simply set it to 0:<br />
 $$V(0)=0$$

← Older revision		Revision as of 15:57, 28 June 2013
Line 8:		Line 8:

	Evaluate the $N$ individuals. Save the best one as $Best$.		Evaluate the $N$ individuals. Save the best one as $Best$.
		+
		+	We will need the volume $V(0)$ of the previous simplex. As no one has been defined yet, we simply set it to 0:<br />
		+	$$V(0)=0$$

@@ Line 1: / Line 1: @@
 == Basic initialisation (i0) ==
+[[Image:Basic APS N vs D.png|right|thumb|400px|Population size vs Dimension]]
 Draw at random $N$ agents (positions) in the search space, according to an uniform distribution.
@@ Line 7: / Line 7: @@
 where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+1$.
-[[File:Basic APS N vs D.png|center]]
+Evaluate the $N$ individuals. Save the best one as $Best$.

← Older revision		Revision as of 19:47, 12 June 2013
Line 1:		Line 1:
−	== Basic ~~APS~~ ==	+	== Basic initialisation (i0) ==

	Draw at random $N$ agents (positions) in the search space, according to an uniform distribution.		Draw at random $N$ agents (positions) in the search space, according to an uniform distribution.

← Older revision		Revision as of 19:05, 11 June 2013
Line 5:		Line 5:
	$N=\max\left(40+2\sqrt{D},\sqrt{40^{2}+\left(D+2\right)^{2}}\right)\label{eq:N_popsize}$		$N=\max\left(40+2\sqrt{D},\sqrt{40^{2}+\left(D+2\right)^{2}}\right)\label{eq:N_popsize}$

−	where $D$ is the dimension of the search space.	+	where $D$ is the dimension of the search space. Note that $N$ needs to be at least equal to $D+1$.
		+
		+	[[File:Basic APS N vs D.png\|center]]

← Older revision		Revision as of 18:49, 11 June 2013
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−	== Basic ~~method~~ ==	+	== Basic APS ==

−	Draw at random N agents (positions) in the search space.	+	Draw at random $N$ agents (positions) in the search space, according to an uniform distribution.
		+
		+	$N=\max\left(40+2\sqrt{D},\sqrt{40^{2}+\left(D+2\right)^{2}}\right)\label{eq:N_popsize}$
		+
		+	where $D$ is the dimension of the search space.

← Older revision		Revision as of 09:18, 11 June 2013
Line 2:		Line 2:


−	== Basic method ==~~<br />~~	+	== Basic method ==
		+
	Draw at random N agents (positions) in the search space.		Draw at random N agents (positions) in the search space.