what'snew.txt

这是一个经典的遗传算法标准源程序

the SxLAB email list is :
SxLAB is a famly of Intelligent algorithms and dynamics simulation tool for Matlab, there are some update info and discussion here.

we talk about : GAs , FLC, ANN, Ant Algorithm, etc., 
                        Dynamics system of vehicle , aero-space , or something related to that.. 

Group email [e-mail]  
Group address Current web address:
http://groups.google.com/group/SxxLAB 

SGALAB 1003 Beta 5.0.0.5

1) Add Micro-GA (muGA) method for Single Objective and Multi-Objective Problem
2) Add Mendel Operator for Single Objective and Multi-Objective Problem
3) add SGALAB_FAQ_QuickStart_2.pdf
4) update SGALAB_FAQ_Genetic Algorithms Brief.pdf

SGALAB 1003 Beta 5.0.0.4

1) Fix SGALAB_demo_TSP_13cities - urgent PR
Variable '1./fitness_plot_max' not found error
2) Fix save figures error       - urgent PR

SGALAB 1003 Beta 5.0.0.3 
1) Fix SGALAB_demo_MO_showall running errors
2) Fix SGA__suspension figure bugs
3) Add multi-axes plots in one figure
4) Add SGALAB_FAQ_Genetic Algorithms Brief
5) Add SGALAB_GTS_SemiactiveSuspension


SGALAB 1003 Beta 5.0.0.2
1) Update SGALAB_FAQ_User's Guide.pdf
2)to fix PR of plot pareto front, 
SGA__pareto_plot_2D
SGA__pareto_replot_2D_MOGA
SGA__pareto_replot_2D_NPGA
SGA__pareto_replot_2D_NSGA
SGA__pareto_replot_2D_NSGAII

SGALAB 1003 Beta 5.0.0.1
1) Update SGALAB_FAQ_WhatisGAs.pdf
2) Update SGALAB_FAQ_User's Guide.pdf
3) Add SGALAB_FAQ_QuickStart.pdf
4) Addpassive suspension model of FLC and skyhook, 
  and GA+FLC and GA+Skyhook control will be avialable in SGALAB 1003 Beta 6

SGALAB 1003 Beta 5
1) NSGA-II ( SGALAB_demo_MO_NSGAII.m )

2) Pareto front plot & show all Multi-Object Methods in SGALAB 
 ( SGALAB_demo_MO_showall.m  )

3) documents updated

4) plot bugs fixed for VEGA,MOGA,NSGA,NPGA

Run 'SGALAB_demo_*.m' to see the demos, and to modify the 'SGALAB_demo_*.m' as your main function for your applications



SGALAB 1003 Beta 4 what's new:
1) Multiple-Objective GAs
VEGA
MOGA
NSGA
NPGA


2) More TSP mutation and Crossover methods
PMX
OX
CX 
EAX
Boolmatrix

3) More selection methods
Truncation
tornament
stochastic

4) mutation methods
binary single point
int/real single point

5) encoding/decoding methods
binary
integer/real
messy
gray
DNA 
permuation