标题: 粒子群算法Matlab工具箱！ [打印本页] 作者: madio 时间: 2020-2-19 08:35 标题: 粒子群算法Matlab工具箱！ PSOt, particle swarm optimization toolbox for matlab. 9 y& y5 p1 o7 s 9 X0 H( O# q6 V) f( p5 AMay be distributed freely as long as none of the files are 2 i; C0 S; [) o/ L/ e0 d
modified. : z8 r, A0 v: |9 a1 {6 J
7 K8 I) s) J8 s2 Z
Send suggestions to bkbirge@yahoo.com 5 f# y' w. J4 u$ ~8 }6 @ 6 o& T7 H; e# `, X/ XUpdates will be posted periodically at the Mathworks User / Q$ ^8 V3 i: ?2 C/ ~2 A
Contributed Files website (www.mathworks.com) under the : U) `2 I+ m) `6 Y
Optimization category.* B/ ^5 z& ~6 n: i( F0 I1 L9 Y0 [
% P# x* M8 W8 A; b
To install: & C- t/ i/ j& [. dExtract into any directory you want but make sure the matlab 0 A% I' u0 r N$ M
path points to that directory and the subdirectories + m' G# {' P+ r9 l! y
'hiddenutils' and 'testfunctions'. % @( c8 Q k1 v; U
9 w H# }' m( I6 ?5 x0 W! k- U
Enjoy! - Brian Birge ; X" o( o/ M9 O: ~& C' C J 2 h6 ?) V4 f+ h0 E G2 X; [------------------------------------------------------------- & K4 D2 H5 v/ l, e! a" s) M------------------------------------------------------------- 5 V' t3 M. U2 }1 f1 t4 G/ F4 A# b 3 K5 y* t1 E; i3 }# @INFO/ }8 Q1 ^+ J2 K$ q6 n6 O* I) ~
Quick start: just type ... out = pso_Trelea_vectorized('f6',2) 0 k% e4 @8 \) _9 Z2 I( m4 t
and watch it work!) V1 L8 s7 O6 B; ~7 Z
6 `* T$ d4 Z9 N- @5 o y1 Z! z% X1 uThis is a PSO toolbox implementing Common, Clerc 1", and / P/ q8 X$ o9 Q* K! f0 rTrelea types along with an alpha version of tracking changing: Z" ~" t/ b w+ Y) _% w# w
environments. It can search for min, max, or 'distance' of & X/ Q1 ]. s8 J
user developed cost function. Very easy to use and hack with 5 ?. ] L4 ~8 y6 ereasonably good documentation (type help for any function and 5 l$ S4 G8 T( ~% T1 x5 `it should tell you what you need) and will take advantage of % \ W2 H7 S( F
vectorized cost functions. It uses similar syntax to Matlab's 8 T/ _# L0 e/ S" t: C z* J# H- S$ {optimization toolbox. Includes a suite of static and dynamic ; ?$ E6 e; Q Itest functions. It also includes a dedicated PSO based neural 2 {$ M# C: ]8 [% {0 Snetwork trainer for use with Mathwork's neural network toolbox. 0 n4 E/ ~3 J; B9 d p, W3 w K- }* N1 A / G0 J( _ r/ j( JRun 'DemoPSOBehavior' to explore the various functions, options, * g' ~% n" I, ?; Rand visualizations. & I; B' D. l+ C& Q5 w) e 8 R+ O, R8 t, f4 T! {Run 'demoPSOnet' to see a neural net trained with PSO H3 A' z# j; `3 L
(requires neural net toolbox).- c f7 d9 h% Q1 T
5 ^: @+ k* [* g6 Y& e" S" ?) j" e5 C4 S# o1 ~5 k8 }: D
This toolbox is in constant development and I welcome " F( p# n4 z1 i5 Gsuggestions. The main program 'pso_Trelea_vectorized.m' lists 3 k1 X+ i" `" X: F7 U, Xvarious papers you can look at in the comments. $ \/ r# ~6 s4 y: X6 Q& Z9 o $ H9 \8 a( h( q5 Y, O3 H. aUsage ideas: to find a global min/max, to optimize training of 4 n( _ p9 x" q4 u% w2 a# n6 }0 fneural nets, error topology change tracking, teaching PSO, ) r% H( U2 N$ K/ F
investigate Emergence, tune control systems/filters, paradigm & F- R" c7 b0 r0 ]/ Y( x+ W k
for multi-agent interaction, etc.7 q& s# e/ J8 }. e
) |8 F2 ~7 v e. A9 P4 k+ T. J/ X-------------------------------------------------------------+ c0 B1 X# |) ~
------------------------------------------------------------- ' a# d' g2 k3 w4 D: ^ {& ^5 g" `+ G9 _- a
1 C. C5 u# g1 ~$ V) KFiles included:) r- P$ O3 d6 E' y* W9 a% u
/ W( u5 D9 d! N
! c$ [) e3 |" S& |** in main directory:3 D8 C1 d' M5 N! U8 D$ J" C
* ]( B0 P7 u; w- n. m: T# q
0) ReadMe.txt - this file, duh - V+ @7 m& g& ]+ \. s2 W1) A Particle Swarm Optimization (PSO) Primer.pdf - powerpoint converted to pdf presentation explaining the very basics of PSO # {4 M3 a" [% ~, z5 y2) DemoPSOBehavior.m - demo script, useful to see how the pso main function is called + ?4 _8 M- \. y1 E9 ^( P7 k3) 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 ) B" @* Q3 D6 I0 L% Y& S7 v- A4) goplotpso.m - default plotting routine used by pso algorithm 1 N. h0 w/ S/ ?% q2 ]4 \8 z5) pso_Trelea_vectorized.m - main PSO algorithm function, implements Common, Trelea 1&2, Clerc 1", and an alpha version of tracking environmental changes. ' M- P5 m: ~$ F" q+ d1 D8 x: c" c( n' u0 U+ E3 O
/ W( g3 m1 z \! c0 z5 E) |$ X- i . `& |) ?' t G( `# F8 x, E** in 'hiddenutils' % t$ w; i! Q; s% h( [1 b ) a( i9 p2 Q) P0 O$ C% q1) 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 ) ~1 ^# e7 _+ |$ h# Z5 ?9 F2) normmat.m - takes a matrix and reformats the data to fit between a new range, very flexible + t: U0 R! S( I/ X5 |3) linear_dyn, spiral_dyn.m - helpers for the dynamic test functions listed in the 'testfunctions' directory . K$ D5 E. O& m$ T0 x, K- f1 i# m2 E+ d8 L
o6 W" ~3 m3 {8 S+ p
. F2 |, C# B, h7 w Y0 ~
** in 'testfunctions' 2 A" d& `# Z" g" s" ^4 B3 A. b3 Z, L2 G
A bunch of useful functions (mostly 2D) for testing. See help for each one for specifics. Here's a list of the names: 3 _) I: [- i& ]& n/ {2 Z ( m( y) H2 {, o% u5 xStatic test functions, minima don't change w.r.t. time/iteration:4 I4 ?0 I" _7 r3 l9 o
1) Ackley7 v. J9 E5 m8 C; ~8 ?0 L" _6 S
2) Alpine 3 p. u; R5 \8 r 3) DeJong_f29 d* E1 V0 |/ y6 M
4) DeJong_f3 2 ~# A$ c j) X6 S. x 5) DeJong_f49 |0 d0 L d# q
6) Foxhole) ]8 m0 g# \* @. ?& h5 O6 }% W2 J# T
7) Griewank & Y5 S+ o; H2 c4 Q 8) NDparabola2 i" e' b" q5 D' R+ R& S/ J
9) Rastrigin , j! M0 j0 g2 L: V5 |* _10) Rosenbrock. [1 ?0 x) r& f: x) @
11) Schaffer f68 Z3 e8 w3 M1 c9 @/ m
12) Schaffer f6 modified (5 f6 functions translated from each other)/ i) b: ^9 M% }0 @1 C
13) Tripod" Q7 `) r* ]: e8 E# z9 @3 ~3 |
/ e% v$ ~1 ` j9 o! s9 \$ vDynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so):( M; f, l! L* P; w
14) f6_bubbles_dyn * j5 A5 _1 H. M: Z15) f6_linear_dyn3 j& Y, \. }6 A8 K5 \3 c+ Z5 _5 u
16) f6_spiral_dyn 3 }/ \. r ?' `% `6 _! }# \4 }, B1 @/ v7 f$ L9 X* W8 ]/ M
$ o* v) G+ f1 Z% {4 G- {7 u' U: u2 [0 v( R' D0 S
** in 'nnet' (all these require Matlab's Neural Net toolbox) $ D0 a* O3 A( C3 E4 ]: ~" y4 d. e- H* ^5 T
1) demoPSOnet - standalone demo to show neural net training% j+ L+ a* |- N) _' \6 A) v
2) trainpso - the neural net toolbox plugin, set net.trainFcn to this7 g0 F; A) N' ]7 U% J/ u7 ~( z
3) pso_neteval - wrapper used by trainpso to call the main PSO optimizer, this is the cost function that PSO will optimize 3 c% e% I$ J9 S d1 o 4) goplotpso4net - default graphing plugin for trainpso, shows net architecture, relative weight indications, error, and PSO details on run' g8 V$ U6 g3 y! j+ @2 a, X
