gatbxa2.ps

基本遗传算法的Matlab工具包

(xovsprs) 135.65 172.95 T
3 F
( ...................................................................................................) 186.02 172.95 T
(2-52) 486.65 172.95 T
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(Genetic Algorithm Toolbox User\325s Guide) 63.65 61.61 T
(2-2) 518.33 61.29 T
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(2 Refer) 63.65 726.29 T
(ence) 150.98 726.29 T
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1.19 (This Section contains detailed descriptions of all of the functions in the Genetic) 135.65 692.95 P
0.55 (Algorithm T) 135.65 678.95 P
0.55 (oolbox. It begins with a list of functions grouped by subject area and) 195.66 678.95 P
5.8 (continues with) 135.65 664.95 P
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5.8 (Refer) 220.53 664.95 P
5.8 (ence) 246.07 664.95 P
3 F
5.8 (entries in alphabetical order) 276.83 664.95 P
5.8 (. Information about) 427.12 664.95 P
(individual functions is also available through the on-line) 135.65 650.95 T
2 F
(Help) 409.48 650.95 T
3 F
( facility) 438.27 650.95 T
(.) 474.46 650.95 T
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(Genetic Algorithm Toolbox User\325s Guide) 63.65 61.61 T
(2-3) 518.33 61.29 T
3 12 Q
(CREA) 262.19 696.95 T
(TING POPULA) 292.85 696.95 T
(TIONS) 369.8 696.95 T
2 F
(crtbase) 141.65 672.95 T
3 F
(create a base vector) 249.65 672.95 T
2 F
(crtbp) 141.65 650.95 T
3 F
(create arbitrary discrete random populations) 249.65 650.95 T
2 F
(crtrp) 141.65 628.95 T
3 F
(create real-valued initial population) 249.65 628.95 T
(FITNESS ASSIGNMENT) 269.85 558.95 T
2 F
(ranking) 141.65 534.95 T
3 F
(generalised rank-based \336tness assignment) 249.65 534.95 T
2 F
(scaling) 141.65 512.95 T
3 F
(proportional \336tness scaling) 249.65 512.95 T
(SELECTION FUNCTIONS) 265.86 442.95 T
2 F
(reins) 141.65 418.95 T
3 F
(uniform random and \336tness-based reinsertion) 249.65 418.95 T
2 F
(rws) 141.65 396.95 T
3 F
(roulette wheel selection) 249.65 396.95 T
2 F
(select) 141.65 374.95 T
3 F
(high-level selection routine) 249.65 374.95 T
2 F
(sus) 141.65 352.95 T
3 F
(stochastic universal sampling) 249.65 352.95 T
(MUT) 267.11 282.95 T
(A) 292.8 282.95 T
(TION OPERA) 300.13 282.95 T
(T) 369.75 282.95 T
(ORS) 376.86 282.95 T
2 F
(mut) 141.65 258.95 T
3 F
(discrete mutation) 249.65 258.95 T
2 F
(mutate) 141.65 236.95 T
3 F
(high-level mutation function) 249.65 236.95 T
2 F
(mutbga) 141.65 214.95 T
3 F
(real-value mutation) 249.65 214.95 T
135.65 712.7 135.65 621.2 2 L
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135.65 574.7 135.65 505.2 2 L
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135.65 458.7 135.65 345.2 2 L
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135.9 434.2 531.4 434.2 2 L
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135.65 298.7 135.65 207.2 2 L
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243.65 271.45 243.65 206.7 2 L
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(Genetic Algorithm Toolbox User\325s Guide) 63.65 61.61 T
(2-4) 518.33 61.29 T
3 12 Q
(CROSSOVER OPERA) 262.62 696.95 T
(T) 374.24 696.95 T
(ORS) 381.35 696.95 T
2 F
(recdis) 141.65 672.95 T
3 F
(discrete recombination) 249.65 672.95 T
2 F
(recint) 141.65 650.95 T
3 F
(intermediate recombination) 249.65 650.95 T
2 F
(reclin) 141.65 628.95 T
3 F
(line recombination) 249.65 628.95 T
2 F
(recmut) 141.65 606.95 T
3 F
(line recombination with mutation features) 249.65 606.95 T
2 F
(recombin) 141.65 584.95 T
3 F
(high-level recombination operator) 249.65 584.95 T
2 F
(xovdp) 141.65 562.95 T
3 F
(double-point crossover) 249.65 562.95 T
2 F
(xovdprs) 141.65 540.95 T
3 F
(double-point reduced surrogate crossover) 249.65 540.95 T
2 F
(xovmp) 141.65 518.95 T
3 F
(general multi-point crossover) 249.65 518.95 T
2 F
(xovsh) 141.65 496.95 T
3 F
(shuf) 249.65 496.95 T
(\337e crossover) 270.08 496.95 T
2 F
(xovshrs) 141.65 474.95 T
3 F
(shuf) 249.65 474.95 T
(\337e reduced surrogate crossover) 270.08 474.95 T
2 F
(xovsp) 141.65 452.95 T
3 F
(single-point crossover) 249.65 452.95 T
2 F
(xovsprs) 141.65 430.95 T
3 F
(single-point reduced surrogate crossover) 249.65 430.95 T
(SUBPOPULA) 257.54 360.95 T
(TION SUPPOR) 326.18 360.95 T
(T) 402.42 360.95 T
2 F
(migrate) 141.65 336.95 T
3 F
(exchange individuals between subpopulations) 249.65 336.95 T
(UTILITY FUNCTIONS) 274.86 266.95 T
2 F
(bs2rv) 141.65 242.95 T
3 F
(binary string to real-value conversion) 249.65 242.95 T
2 F
(rep) 141.65 220.95 T
3 F
(matrix replication) 249.65 220.95 T
135.65 712.7 135.65 423.2 2 L
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(Genetic Algorithm Toolbox User\325s Guide) 63.65 61.61 T
(2-5) 518.33 61.29 T
63.65 716.95 531.65 726.95 C
63.65 725.95 531.65 725.95 2 L
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-8.35 24.95 603.65 816.95 C
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(bs2rv) 63.65 732.95 T
1 16 Q
(Purpose) 117.65 692.29 T
3 12 Q
(binary string to real value conversion) 135.65 674.95 T
1 16 Q
(Synopsis) 117.65 646.29 T
2 12 Q
(Phen = bs2rv\050Chrom, FieldD\051) 135.65 628.95 T
1 16 Q
(Description) 117.65 606.29 T
2 12 Q
1.31 (Phen = bs2rv\050Chrom, FieldD\051) 135.65 588.95 P
3 F
0.55 ( decodes the binary representation of the) 333.87 588.95 P
5.26 (population,) 135.65 574.95 P
2 F
12.62 (Chrom) 198.21 574.95 P
3 F
5.26 (, into vectors of reals. The chromosomes are seen as) 234.19 574.95 P
0.28 (concatenated binary strings of given length, and decoded into real numbers over a) 135.65 560.95 P
1.93 (speci\336ed interval using either standard binary or Gray coding according to the) 135.65 546.95 P
8.28 (decoding matrix,) 135.65 532.95 P
2 F
19.86 (FieldD) 236.48 532.95 P
3 F
8.28 (. The resulting matrix,) 279.65 532.95 P
2 F
19.86 (Phen) 422.69 532.95 P
3 F
8.28 (, contains the) 451.47 532.95 P
(corresponding population phenotypes.) 135.65 518.95 T
0.12 (The use of Gray coding for binary chromosome representation is recommended as) 135.65 492.95 P
-0.23 (the regular Hamming distance between quantization intervals reportedly makes the) 135.65 478.95 P
-0.12 (genetic search less deceptive \050see, for example, [1, 2]\051. An option to set the scaling) 135.65 464.95 P
2.54 (between quantization points can be used to select either linear or logarithmic) 135.65 450.95 P
-0.17 (decoding to real values from binary strings. Logarithmic scaling is useful when the) 135.65 436.95 P
0.26 (range of decision variable is unknown at the outset as a wider range of parametric) 135.65 422.95 P
3.55 (values can be searched with fewer bits [3], thus reducing the memory and) 135.65 408.95 P
(computational requirements of the GA.) 135.65 394.95 T
(The matrix) 135.65 368.95 T
2 F
(FieldD) 191.61 368.95 T
3 F
( has the following structure:) 234.79 368.95 T
(,) 356.55 294.72 T
(where the rows of the matrix are composed as follows:) 135.65 221.66 T
2 F
3.26 (len) 135.65 195.66 P
3 F
1.36 (, a row vector containing the length of each substring in) 157.24 195.66 P
2 F
3.26 (Chrom) 442.65 195.66 P
3 F
1.36 (. Note that) 478.63 195.66 P
2 F
(sum\050len\051) 135.65 181.66 T
3 F
( should equal) 193.22 181.66 T
2 F
(length\050Chrom\051) 260.18 181.66 T
3 F
(.) 353.72 181.66 T
2 F
-0.15 (lb) 135.65 155.66 P
3 F
-0.06 ( and) 150.04 155.66 P
2 F
-0.15 (ub) 173.23 155.66 P
3 F
-0.06 ( are row vectors containing the lower and upper bounds respectively for) 187.62 155.66 P
(each variable used.) 135.65 141.66 T
2 F
4.76 (code) 135.65 115.66 P
3 F
1.98 ( is a binary row vector indicating how each substring is decoded. Select) 164.43 115.66 P
2 F
(code\050i\051 = 0) 135.65 101.66 T
3 F
( for standard binary and) 214.8 101.66 T
2 F
(code\050i\051 = 1) 332.38 101.66 T
3 F
( for Gray coding.) 411.53 101.66 T
307.75 243.66 356.55 350.95 C
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(l) 321.15 335.96 T
(e) 329.05 335.96 T
(n) 336.95 335.96 T
(l) 325.1 321.49 T
(b) 333 321.49 T
(u) 325.1 307.02 T
(b) 333 307.02 T
(c) 317.2 292.55 T
(o) 325.1 292.55 T
(d) 333 292.55 T
(e) 340.9 292.55 T
(s) 313.25 278.08 T
(c) 321.15 278.08 T
(a) 329.05 278.08 T
(l) 336.95 278.08 T
(e) 344.86 278.08 T
(l) 317.2 263.61 T
(b) 325.1 263.61 T
(i) 333 263.61 T
(n) 340.9 263.61 T
(u) 317.2 249.14 T
(b) 325.1 249.14 T
(i) 333 249.14 T
(n) 340.9 249.14 T
314.75 246.66 310.75 246.66 2 L
0.33 H
0 Z
N
310.75 246.66 310.75 347.95 2 L
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310.75 347.95 314.75 347.95 2 L
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349.55 246.66 353.55 246.66 2 L
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353.55 347.95 349.55 347.95 2 L
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-8.35 24.95 603.65 816.95 C
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(Genetic Algorithm Toolbox User\325s Guide) 63.65 61.61 T
(2-6) 518.33 61.29 T
2 12 Q
9.44 (scale) 135.65 736.95 P
3 F
3.93 ( is a binary row vector indicating whether to use arithmetic and/or) 171.63 736.95 P
1.68 (logarithmic scaling for each substring. Select) 135.65 722.95 P
2 F
4.03 (scale\050i\051 = 0) 365.25 722.95 P
3 F
1.68 ( for arithmetic) 459.67 722.95 P
(scaling and) 135.65 708.95 T
2 F
(scale\050i\051 = 1) 192.94 708.95 T
3 F
( for logarithmic scaling.) 279.29 708.95 T
2 F
0.93 (lbin) 135.65 682.95 P
3 F
0.39 ( and) 164.43 682.95 P
2 F
0.93 (ubin) 188.52 682.95 P
3 F
0.39 ( are binary row vectors indicating whether or not to include each) 217.3 682.95 P
2.86 (bound in the representation range. Select) 135.65 668.95 P
2 F
6.86 ({l|u}bin\050i\051 = 0) 351.65 668.95 P
3 F
2.86 ( to exclude) 473.3 668.95 P
2 F
0.9 ({l|u}b\050i\051) 135.65 654.95 P
3 F
0.38 ( from the representation range and) 200.41 654.95 P
2 F
0.9 ({l|u}bin\050i\051 = 1) 370.52 654.95 P
3 F
0.38 ( to include) 480.26 654.95 P
2 F
({l|u}b\050i\051) 135.65 640.95 T
3 F
( in the representation range.) 200.41 640.95 T
1 16 Q
(Example) 117.65 612.29 T
3 12 Q
2.8 (Consider the following binary population, created using the) 135.65 594.95 P
2 F
6.73 (crtbp) 446.89 594.95 P
3 F
2.8 ( function,) 482.87 594.95 P
2.25 (representing a set of single decision variables in the range [-1, 10]. The code) 135.65 580.95 P
1.74 (extract shows how the function) 135.65 566.95 P
2 F
4.17 (bs2rv) 297.24 566.95 P
3 F
1.74 ( may be used to convert the Gray code) 333.22 566.95 P
(binary representation to real-valued phenotypes using arithmetic scaling.) 135.65 552.95 T
2 F
(Chrom = crtbp\0504,8\051 % create random chromosomes) 135.65 532.95 T
(Chrom =) 135.65 512.95 T
(0 0 0 0 0 1 1 1) 153.65 498.95 T
(1 0 0 0 1 0 0 1) 153.65 484.95 T
(0 0 1 0 1 0 0 0) 153.65 470.95 T
(1 1 0 1 1 0 1 1) 153.65 456.95 T
(FieldD = [8; -1; 10; 1; 0; 1; 1]; % representation) 135.65 436.95 T
(Phen = bs2rv\050Chrom,FieldD\051 % convert binary to real) 135.65 416.95 T
(Phen =) 135.65 396.95 T
(-0.7843) 153.65 382.95 T
(9.3961) 160.84 368.95 T
(1.0706) 160.84 354.95 T
(5.2980) 160.84 340.95 T
1 16 Q