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درس تئوری تصمیم گیری (1)

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Hossein Zeinivand
Hossein Zeinivand

درس تئوری تصمیم گیری

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‫تĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬ
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ 1‫تتتتتتت‬ . ‫تتتتتتتتت‬ ‫تتتتت‬ ‫تت‬ 2‫تتتتت‬ . ‫ت‬ ‫تتتتت‬ ‫تتتت‬ 3‫تتتتت‬ . ‫تت‬ ‫تتت‬ ‫تت‬4. ‫تتتتت‬ ‫ت‬ 5. ‫تتتت‬ ‫تتت‬ ‫ت‬ ‫تت‬ 6. ‫تتتت‬ ‫ت‬ ‫تتت‬ ‫تتتت‬ ‫تت‬ ‫تتتت‬ ‫تت‬ ‫تتتت‬ ‫ت‬ ‫تتتت‬
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬  
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ ‫تتت‬ ‫تتت‬ ‫تت‬ ‫تتتت‬ ‫تت‬ ‫تتت‬ ‫تتتت‬ ‫تتتتت‬
)‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬MCDM( ‫تتتت‬ ‫تتتتت‬ ‫تتتتتتت‬ ‫تĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬ‫تĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬ‫تĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬ‫تĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬīتĬ‫ت‬
n )xn( ... 2 )x2( 1 )x1( r1n … r12 r11 1(A1) r2n … r22 r21 2(A2) … … … … ... rmn … rm2 rm1 m (Am) m
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ Objective) Attribute)
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬:‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬   MODM
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ ‫ت‬‫ت‬‫ت‬‫ت‬:‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬    MADM
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬    
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬  ‫تتتتت‬ ‫تتت‬‫تتتت‬ ‫تتت‬  
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ 
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ 1. 2. 3. 4. 5. 6. 7. 0
‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬ 4
1‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬.      
1.1‫صصصص‬ ‫صصصصصصص‬ . ‫صصصص‬ ‫ص‬ ‫صصص‬ ‫صصص‬      
3.1‫صصص‬ ‫صصصص‬ ‫صصصصصصص‬ . ‫صصصص‬ ‫ص‬ ‫صصصص‬ ‫صصصص‬ ‫صص‬ 2     
2.1‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬.  0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10
2‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬. 4
3‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬.  
1.3‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬. n )xn( ... 2 )x2( 1 )x1( r1n … r12 r11 1(A1) r2n … r22 r21 2(A2) … … … … ... rmn … rm2 rm1 m (Am)
4‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬. 10 15 1 7 4 7 3 12 2 9 5 5 20 3 5 30 3 9 1 30 4 3 1 3
5‫صĬīصĬīصĬīصĬīصĬīصĬīصĬīصĬīصĬīصĬīصĬ.
1.5‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬- ∑= = m i ij ij ij r r n 1 2
∑= 4 1 2 i ija 7 1 0 4 7 15 1 0.547 0 . 3 1 5 0.560 0.547 0.367 9 3 5 5 12 2 0 . 853.40 30201215 2222 4 1 2 1 =+++ =∑=i ir 294.0 853.40 12 367.0 853.40 15 21 11 == == n n 1.5(‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬)‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬-
2.5‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬.    ij ij ij rMax r n = ij ij ij rMax r n 1−= ) 1 ( 1 ij ij ij r Max r n =
6‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬.     Wn … W2 W1 xn ... x2 x1 r1n … r12 r11 A1 r2n … r22 r21 A2 … … … … ... rmn … rm2 rm1 Am
1.6‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬- ji,; 1 ∀= ∑= n i ij ij ij a a P )(ln 1 m k = [ ] j;ln 1 ∀−= ∑= m i ijijj ppkE j;1 ∀−= jj Ed j d d w n j j j j ∀= ∑= ; 1
7 10 4 7 15 1 0.292 0.227 0.308 0.292 0.195 9 3 5 5 12 2 0.375 0.068 0.384 0.208 0.156 5 30 3 9 20 3 0.208 0.682 0.231 0.375 0.260 3 1 1 3 30 4 0.125 0.023 0.077 0.125 0.389 24 44 13 24 77 Pij 77=30+20+12+15 0.195=77/15 1.6(‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬)‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬-
Ej 721.0 )4ln( 1 )ln( 1 === m k E1 E2 E3 E4 E5 0.956 0.947 0.913 0.625 0.947 956.0)]389.0ln(*389.0)260.0ln(*260.0 )156.0ln(*156.0)195.0ln(*195.0[721.01 =+ ++−=E dj d1 d2 d3 d4 d5 1-Ej 0.04 4 0.05 3 0.08 7 0.37 5 0.05 3 0.61 2 072.0 612.0 044.01 1 === ∑ jd d wW1 W2 W3 W4 W5 0.072 0.087 0.142 0.613 0.087 1.6(‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬)‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬‫ص‬-
2.6‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬- Aa[i,jWi/Wja[i,j          = =+ =+ 0),( 0 0 yxg y g y f x g x f δ δ λ δ δ δ δ λ δ δ ( ) nl n j lwjwlja n i ilaiwlwila n i n j n i iwiwjwjiaL n i iWst n i n j iwjwijaz ,...,2,10 1 )( 1 )( 1 1 1 1 22),( 1 1 : 1 1 2)()min( ==+∑ = −−∑ = − ∑ = ∑ = −∑ = +−= =∑ = ∑ = ∑ = −= λ λ ),(),( yxgyxfu λ+=
2206.0 6059.0 1735.0 1 0 4 45 3 10 2 5 0 3 10 9 20 3 10 0 2 5 3 1015 13. 3 1.) 2 1(3, 3 1 .|,, 1 3 12 313 2 1 3 11 3 2 1 321 321 321 321 2312132312 ,, = = = =++ =++−− =+−+− =+−− ==≠=⇒== ≠∃           = w w w www www www www aaaaa aaakji A jijkik λ λ λ (‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬)‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬
3.6‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬- nnnnnn nn nn WWaWaWa WWaWaWa WWaWaWa . . . 2211 22222121 11212111 λ λ λ =+++ =+++ =+++     WA WWA .λ=× n 0)det( =− IA λ 0)( max =×− WIA λ        =                         nnnnn n n w w w aaa aaa aaa : ... :...:: ... ... 2 1 21 22221 11211
)2493.0,5936.0,1571.0( 1 0 0536.2 3 12 30536.23 2 1 3 10536.2 0)(0536.3 0 2 5)1(3)1( 1 3 12 313 2 1 3 11 )det( 1 3 12 313 2 1 3 11 321 3 2 1 maxmax 3 = =++ =                     − − − =−= =+−−−= − − − =−           = T W www w w w WIA IA A λλ λλ λ λ λ λ (‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬)‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬
7‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬‫ت‬.  SAW ELECTRE TOPSIS LINMAP AHP
A1 3.0 5 9 24000 1 A2 1.2 7 5 25000 3 A3 1.5 9 3 32000 7 A1 1 1 1.00 0.75 1 A2 0.4 0.71 0.55 0.78 0.33 A3 0.43 0.55 0.33 1.00 0.14 Min =0.75 Min =0.33 Min =0.14 Max { min } = 0.75 A1 2Maxi min minmin max
‫تت‬ ‫تتتت‬ ‫تت‬ ‫تتتتت‬ ‫تت‬ ‫تتتتت‬ ‫تتتت‬ ‫تتتتت‬ ‫تت‬ ‫ت‬ ‫ت‬ ‫تتتت‬ ‫ت‬ ‫تت‬ ‫ت‬ ‫ت‬ ‫تتتت‬ ‫تت‬ ‫ت‬ ‫ت‬ ‫تتتت‬Max‫تتتت‬ ‫تت‬ ‫ت‬ ‫ت‬ ‫ت‬ ‫تتت‬ ‫تتتتتتت‬ ‫تت‬ ‫ت‬ ‫ت‬ ‫تتتت‬Max‫تت‬ .‫تتتت‬ ‫تت‬ ‫تتتتتت‬ Max =1 Max =0.78 Max =0.14 Max { max } = 1 A1A3 A1 3.0 5 9 24000 1 A2 1.2 7 5 25000 3 A3 1.5 9 3 32000 7 A1 1 1 1.00 0.75 1 0.780.33A2 0.4 0.71 0.55 A3 0.43 0.55 0.33 1.00 0.14
4)Conjunctive( DM
5Disjunctive conjunctive DM
n.imanipour,2008 )ordinal( 
1.7-SAW       = ∑= n j jiji wnMaxAA 1 * |           =                           696.0 749.0 529.0 234.0 263.0 076.0 189.0 239.0 * 1333.0115.0 778.0556.0778.06.01 333.01556.04.0333.0 Simple Additive Weighting method
2.7-TOPSIS N W VnnWNV **= + jV − jV + jd − jd +− − + = ii i i dd d CL* V V m1,2,...,i,)( m1,2,...,i,)( 1 2 1 2 =−= =−= ∑ ∑ = −− = ++ n j jiji n j jiji vvd vvd * iCLCL Technique for Order-Preference by Similarity to Ideal Solution
          =                       149.0119.0063.0238.0 099.0179.0052.0119.0 198.0258.0042.0149.0 267.0000 0336.000 00092.00 000305.0 * 557.0355.0684.0781.0 371.0532.0570.0390.0 743.0769.0456.0488.0 C1 C2 C3 C4 A1 5 8 13 4 A2 4 10 9 2 A3 8 12 6 3 V .198]63,0.258,0[0.119,0.0],,,[ 4321 ==+ iiiij vMaxvMaxvMaxvMinV .099]42,0.119,0[0.238,0.0],,,[ 4321 ==− iiiij vMinvMinvMinvMaxV 2.7-TOPSIS)‫(تتتتت‬
189.0 127.0 037.0 3 2 1 = = = + + + d d d 055.0 134.0 192.0 3 2 1 = = = − − − d d d 037.0)198.0198.0()258.0258.0()063.0042.0()119.0149.0( 2222 1 =−+−+−+−=+ d 225.0 513.0 838.0 * 3 * 2 * 1 = = = CL CL CL 838.0 037.0192.0 192.0* 1 = + =CL 2.7-TOPSIS)‫(تتتتت‬
4.7-AHP )Analytical Hierarchy process-AHP(1980 Analytic Hierarchy Process
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ Reciprocal Condition( ABnBAn/1 Homogeneity( ABAB Dependency( Expectation(
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ 1234
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ n ... 2 1 1)x1( 2)x2( ... m (xm( 1 3 5 7 9 2468
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬  ABBCAC a[i,k].a[k,j]=a[i,jijk 1.0
(‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ CBA
1 3 2 2 3/1 1 4/1 4/1 2/1 4 1 2/1 2/1 4 2 1 2.33 12 5.25 3.7 5 0.43 0.25 0.38 0.5 3 0.39 8 0.14 0.08 0.05 0.0 7 0.08 5 0.21 0.33 0.19 0.1 3 0.21 8 0.21 0.33 0.38 0.2 7 0.29 9 (‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬
A B C A 1 2 8 0.59 3 B 2/1 1 6 0.34 1 C 8/1 6/1 1 0.06 6 A B C A 0.1 23 B 0.3 20 C 0.5 57 A B C A 0.08 7 B 0.27 4 A B C A 0.26 5 B 0.65 5 (‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬
0.398 0.085 0.218 0.29 9 A 0.123 0.087 0.593 0.26 5 0.265 B 0.320 0.274 0.341 0.65 5 0.421 C 0.557 0.639 0.066 0.08 0 0.314 0.265=0.265*0.299+0.593*0.218+0.087*0.085+0.123*0.398A (‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ An n nλλλ ,,, 21  n n i i =∑=1 λ n≥maxλ maxλ
nn (‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ 1 .. max − − = n n II λ ... .. .. RII II RI = n 1 2 3 4 5 6 7 8 9 10 I.I.R. 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.45 maxλ maxλ
(‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ 1.A 2.W. 3.A 1-3-WA 2-3-W 3-3- 4. 5. maxλ WmaxλWAW maxλ= Wmaxλmaxλ maxλ
017.0 58.0 01.0 ... .. .. 010.0 13 3019.3 1 .. 019.3 3 985.2 066.0 197.0 032.3 341.0 034.1 040.3 593.0 803.1 066.0 341.0 593.0 * 197.0 034.1 803.1 066.0 341.0 593.0 * 1 6 1 8 1 61 2 1 821 066.0 341.0 593.0 1 6 1 8 1 61 2 1 821 3*3 max 3max2max1max max 3max 2max 1max max === = − − = − − = = ++ = == == ==           =           =                       =           =             = RII II RI n n II AW WA λ λλλ λ λ λ λ λ ‫ي‬ (‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬)‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬    
‫ي‬‫ي‬‫ي‬‫ي‬‫ي‬ 1.""1382 2.1384 3.1381 4.1385 5.1381 6.1378 7.1385 8. 9.

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