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. - R5 S/ \. ]( v" D% O7 d3 w - ~! ~( ^% e4 B* v' p6 MMay be distributed freely as long as none of the files are 1 A' n) F6 ^# R5 N$ \) b" k9 s4 qmodified. 6 R3 L* U9 [6 H2 }; ^1 B
3 [2 p8 X0 q/ b" [* ?% ^, X" A! mSend suggestions to bkbirge@yahoo.com 7 X9 x. ]% e" h X+ I/ r; y. A% ~" n# N b
Updates will be posted periodically at the Mathworks User ) S: d2 x5 {! {9 c" B- {
Contributed Files website (www.mathworks.com) under the 7 _: z1 g0 i! c$ B1 ~. U) XOptimization category.* v* Z5 b0 H$ N c
7 H+ s- n; u J @ pTo install: 8 H2 \4 M9 R8 D4 a& {6 iExtract into any directory you want but make sure the matlab 3 X1 t- p( P% t& G9 I
path points to that directory and the subdirectories ; e7 K h% c& y. `" C) q1 r0 r/ L
'hiddenutils' and 'testfunctions'. 5 D- l) v, z0 P( V
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Enjoy! - Brian Birge 7 [# v6 j5 e' E" h7 Y ' f5 D3 l# h( _* P------------------------------------------------------------- / d2 y/ [& d* S6 J+ m. c------------------------------------------------------------- + K8 ]: y4 h3 x, x* k% s . [8 P, Q ^! t, @& q7 F4 `INFO ; A9 ^7 I/ F+ h# x$ C5 C% PQuick start: just type ... out = pso_Trelea_vectorized('f6',2) % S+ T, D# E- Xand watch it work!. _5 O- R; @& r9 o* d o- }& g
( A, ?# C8 W) \: {This is a PSO toolbox implementing Common, Clerc 1", and 7 k9 ~" L3 _, p* H2 nTrelea types along with an alpha version of tracking changing 1 e9 }4 A7 P& D5 Q# U. B6 @environments. It can search for min, max, or 'distance' of ' P! p& Z8 _' A& }8 huser developed cost function. Very easy to use and hack with 8 i" h8 b8 U! [9 mreasonably good documentation (type help for any function and 5 m0 U: T# _! p5 d# n0 Z5 Y/ Eit should tell you what you need) and will take advantage of 4 E7 r+ B$ u' c. p+ W1 E. m! p; nvectorized cost functions. It uses similar syntax to Matlab's 8 k1 {7 {/ s' i. y1 e. o0 Joptimization toolbox. Includes a suite of static and dynamic ) Q( y6 H& p8 T; R" |2 m- n; c
test functions. It also includes a dedicated PSO based neural / C' g F7 l7 I* y- r0 {0 bnetwork trainer for use with Mathwork's neural network toolbox. 4 v8 q/ S& G1 w2 }0 v: y F3 U& m1 k) I+ m. ^+ Y7 p
Run 'DemoPSOBehavior' to explore the various functions, options, : a! n: c$ O" R, G
and visualizations. - ~ O' j) \0 n/ p: x7 d8 }$ D& ]
* ^0 X* N6 m" w) oRun 'demoPSOnet' to see a neural net trained with PSO 0 J1 ] @( |4 o9 P" O* a(requires neural net toolbox).% z# d, Y h6 h- p7 `
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This toolbox is in constant development and I welcome 1 w2 w. T9 p* z3 h# H. |7 rsuggestions. The main program 'pso_Trelea_vectorized.m' lists : A9 k# u0 e7 P8 A$ `various papers you can look at in the comments.) M8 L: t$ G1 h/ v7 Z
$ w. q: j/ _+ T/ X' u2 ~' d( _Usage ideas: to find a global min/max, to optimize training of # M( j8 _) a R) I6 u* k5 T$ @3 \: R
neural nets, error topology change tracking, teaching PSO, 7 q/ N3 }* w* ^* d( i; v4 d; D, J, W
investigate Emergence, tune control systems/filters, paradigm 6 B/ Z0 R+ N: Z2 B3 ?2 G% Ufor multi-agent interaction, etc.& H M1 _; h2 n) O# A! `7 S# O k
: z0 Q% _% D1 i8 S------------------------------------------------------------- 3 M, ?% {0 V& X' [- K------------------------------------------------------------- ) L& @' O9 t, X( H % k! t& h- V! w$ T" I" t. X 3 I; B7 V. E- v+ h/ L+ L a* ?Files included: ' ]' s$ N4 v) i' `! u7 M. c3 D& K5 K/ u( p
* @: G% K4 w' [) ?1 ]; C& u) I** in main directory:5 R b; m2 {; T7 h. x
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0) ReadMe.txt - this file, duh( W% b- i4 g Q. P5 \
1) A Particle Swarm Optimization (PSO) Primer.pdf - powerpoint converted to pdf presentation explaining the very basics of PSO, m% F2 V6 H( Z l* u
2) DemoPSOBehavior.m - demo script, useful to see how the pso main function is called+ l2 h- I: V- t1 H) u7 ^5 F$ z
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 - d; j5 m7 v' P: X& t: j4) goplotpso.m - default plotting routine used by pso algorithm! a+ \8 E4 \2 n: T& E- v9 `
5) pso_Trelea_vectorized.m - main PSO algorithm function, implements Common, Trelea 1&2, Clerc 1", and an alpha version of tracking environmental changes.4 N+ f( s! J6 U0 p- c7 J0 F
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** in 'hiddenutils'+ W" }7 [, ?! |; @/ X! ]
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1) 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 + E* _% ]4 q/ A& L2) normmat.m - takes a matrix and reformats the data to fit between a new range, very flexible9 k( i' R G ^) l2 @" f
3) linear_dyn, spiral_dyn.m - helpers for the dynamic test functions listed in the 'testfunctions' directory / q' B5 a K- s' i) w4 y- I, n4 n& L. T# g* p1 g
1 \- F# l1 k0 s7 Z ) s; a# i8 \- q* |3 M; `1 u& }** in 'testfunctions'7 I0 K: i1 O6 [: q m8 N
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A bunch of useful functions (mostly 2D) for testing. See help for each one for specifics. Here's a list of the names:) _! r2 i- e1 n7 {
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Static test functions, minima don't change w.r.t. time/iteration: 7 B4 m5 _+ x6 x( {1 ~1 k7 E2 l8 } 1) Ackley , I6 \" O4 z# V6 j: p) u 2) Alpine! y" c+ u; Y8 V$ _7 H
3) DeJong_f26 h; J0 J v) J7 Q& ~( @9 ^" w
4) DeJong_f3 & F0 g7 {' E" Y9 o: J) R 5) DeJong_f4 / i$ o8 L+ e" V/ n# M7 E 6) Foxhole9 V) y. k; ]+ ?, m* U' A$ ]
7) Griewank( U; R* W* U4 G
8) NDparabola# X7 d& r2 D! m) ^- U1 y
9) Rastrigin 8 ]2 Q8 M! ?7 V" K! E1 |) [10) Rosenbrock) P, s. J8 u+ a. u% _# H
11) Schaffer f61 _) k6 V0 Y8 T5 L% R
12) Schaffer f6 modified (5 f6 functions translated from each other)( ^$ J3 ~2 T; ^$ d- i, e0 b
13) Tripod' [9 A# [4 ?) H4 u% p4 f0 L. d
t Q, q, o0 P4 D$ c5 ^8 p0 gDynamic test functions, minima/environment evolves over time (NOT iteration, though easily modifed to do so): x e" c+ i2 u6 M/ u' U- A2 F
14) f6_bubbles_dyn & {# h) y2 ?# T15) f6_linear_dyn+ w6 H1 Z t# a$ B% G/ L
16) f6_spiral_dyn 5 _ o' V$ J" F% ~% T7 v! d1 |$ h0 c6 {0 ^/ C& A E
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** in 'nnet' (all these require Matlab's Neural Net toolbox)8 X; K. C, v9 p( W
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1) demoPSOnet - standalone demo to show neural net training0 Y# o, @6 {; n
2) trainpso - the neural net toolbox plugin, set net.trainFcn to this % q6 Z: Y# \$ n- V. R 3) pso_neteval - wrapper used by trainpso to call the main PSO optimizer, this is the cost function that PSO will optimize* m- q4 O5 a0 f" K! U1 D+ C
4) goplotpso4net - default graphing plugin for trainpso, shows net architecture, relative weight indications, error, and PSO details on run 3 g1 m3 S$ f! [% ~: T, K* V* K) I! O5 P
