粒子群算法Matlab工具箱！

madio

PSOt, particle swarm optimization toolbox for matlab.
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  c  F7 c8 K8 [2 q4 t4 MMay be distributed freely as long as none of the files are
. u1 R4 |, v& i0 `+ qmodified.
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7 |* X" p  ?0 S# BSend suggestions to bkbirge@yahoo.com

' U8 _: n0 H1 |7 ~  J% _" l, cUpdates will be posted periodically at the Mathworks User
6 r) v  |5 y+ T: ^% jContributed Files website (www.mathworks.com) under the
8 d& F+ z  u! @& G2 gOptimization category.
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To install:
& o% E9 f+ q% k  J" `2 G- f- tExtract into any directory you want but make sure the matlab
- X) [8 v6 G* bpath points to that directory and the subdirectories
'hiddenutils' and 'testfunctions'.
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Enjoy! - Brian Birge
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  [7 E6 }4 g& @-------------------------------------------------------------
-------------------------------------------------------------

INFO
$ m7 |6 y. v) f: z! B( I$ b& qQuick start: just type ... out = pso_Trelea_vectorized('f6',2)
2 ~- P2 b+ |4 R+ g8 a* Zand watch it work!
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5 `# E) @2 _- s, e! H  OThis is a PSO toolbox implementing Common, Clerc 1", and
Trelea types along with an alpha version of tracking changing
& v+ F4 c; R1 y! d7 l# xenvironments. It can search for min, max, or 'distance' of
user developed cost function. Very easy to use and hack with
reasonably good documentation (type help for any function and
! Z; E; @% I4 @" ?# K  e: I$ Zit should tell you what you need) and will take advantage of
+ g$ N! M  P/ z: f* r$ \vectorized cost functions. It uses similar syntax to Matlab's
5 }9 ?5 g2 R$ {$ [$ @5 l9 L3 ioptimization toolbox. Includes a suite of static and dynamic
test functions. It also includes a dedicated PSO based neural
network trainer for use with Mathwork's neural network toolbox.

Run 'DemoPSOBehavior' to explore the various functions, options,
and visualizations.
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' I* P6 b  u) ~1 y, w3 gRun 'demoPSOnet' to see a neural net trained with PSO
6 v9 X$ \; I- Q2 Z: k/ B" y' B(requires neural net toolbox).
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* t7 i6 v2 c; l$ s4 hThis toolbox is in constant development and I welcome
$ _/ c% D6 O$ i9 r' M: Fsuggestions. The main program 'pso_Trelea_vectorized.m' lists
various papers you can look at in the comments.
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% ?- `3 @$ Q* t* I9 z5 t8 G; G( oUsage ideas: to find a global min/max, to optimize training of
neural nets, error topology change tracking, teaching PSO,
+ s) G2 Z/ F* e; F: P7 k3 z' A, ]investigate Emergence, tune control systems/filters, paradigm
for multi-agent interaction, etc.

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; y5 d( U" j3 R( N3 d0 A) h# lFiles included:

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** in main directory:
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) t, x& @% \3 m( x4 d1 W7 L( {9 y* U0) ReadMe.txt - this file, duh
1) A Particle Swarm Optimization (PSO) Primer.pdf  -  powerpoint converted to pdf presentation explaining the very basics of PSO
2) DemoPSOBehavior.m - demo script, useful to see how the pso main function is called
3) goplotpso4demo.m - plotting routine called by the demo script, useful to see how custom plotting can be developed though this routine slows down the PSO a lot
4) goplotpso.m - default plotting routine used by pso algorithm
5) pso_Trelea_vectorized.m - main PSO algorithm function, implements Common, Trelea 1&2, Clerc 1", and an alpha version of tracking environmental changes.

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8 D. }5 Q7 j+ m) ]9 a. P** in 'hiddenutils'

& `0 _5 s3 `/ Q0 P) q  ?3 h+ C! o1) forcerow, forcecol.m - utils to force a vector to be a row or column, superseded by Matlab 7 functions I believe but I think they are still called in the main algo
, F; b4 {6 E0 M0 f2) normmat.m - takes a matrix and reformats the data to fit between a new range, very flexible
2 v: R, D+ a5 ^' b" z/ e3) linear_dyn, spiral_dyn.m - helpers for the dynamic test functions listed in the 'testfunctions' directory
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** in 'testfunctions'

6 L, S+ ^- A5 V$ c2 b% ?5 iA bunch of useful functions (mostly 2D) for testing. See help for each one for specifics. Here's a list of the names:

$ O8 c& b2 F/ @5 zStatic test functions, minima don't change w.r.t. time/iteration:
1) Ackley
2) Alpine
" X% C" B- \$ U* w 3) DeJong_f2
6 A& Y3 n2 n+ f4 A3 D$ N 4) DeJong_f3
5) DeJong_f4
9 H' ~. S- a: U 6) Foxhole
7) Griewank
  k) k' P2 C( U 8) NDparabola
9) Rastrigin
10) Rosenbrock
+ D  G! M4 m$ E2 v6 N11) Schaffer f6
12) Schaffer f6 modified (5 f6 functions translated from each other)
13) Tripod

Dynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so):
' o- ^% |* {3 X; |1 T: s# U4 K14) f6_bubbles_dyn
15) f6_linear_dyn
) q$ I4 u4 {) J1 j16) f6_spiral_dyn
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** in 'nnet' (all these require Matlab's Neural Net toolbox)

1) demoPSOnet - standalone demo to show neural net training
2) trainpso   - the neural net toolbox plugin, set net.trainFcn to this
3) pso_neteval - wrapper used by trainpso to call the main PSO optimizer, this is the cost function that PSO will optimize
4) goplotpso4net - default graphing plugin for trainpso, shows net architecture, relative weight indications, error, and PSO details on run


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