Engineering Optimization: Theory and Practice, Fourth Edition

(Martin Jones) #1
5.5 Dichotomous Search 259

whereδ is a small quantity, say 0.001, andnis the number of experiments. If the
middle point of the final interval is taken as the optimum point, the requirement can
be stated as
1
2


Ln
L 0


1

10

i.e.,
1
2 n/^2


+

δ
L 0

(

1 −

1

2 n/^2

)


1

5

Sinceδ= 0 .001 andL 0 = 1. 0 , we have


1
2 n/^2

+

1

1000

(

1 −

1

2 n/^2

)


1

5

i.e.,
999
1000


1

2 n/^2


995

5000

or 2n/^2 ≥

999

199

≃ 5. 0

Sincenhas to be even, this inequality gives the minimum admissible value ofnas 6.
The search is made as follows. The first two experiments are made at


x 1 =

L 0

2


δ
2

= 0. 5 − 0. 0005 = 0. 4995

x 2 =

L 0

2

+

δ
2

= 0. 5 + 0. 0005 = 0. 5005

with the function values given by


f 1 =f(x 1 )= 0. 4995 (− 1. 0005 )≃ − 0. 49975
f 2 =f(x 2 )= 0. 5005 (− 0. 9995 )≃ − 0. 50025

Sincef 2 < f 1 , the new interval of uncertainty will be (0.4995, 1.0). The second pair
of experiments is conducted at


x 3 =

(

0. 4995 +

1. 0 − 0. 4995

2

)

− 0. 0005 = 0. 74925

x 4 =

(

0. 4995 +

1. 0 − 0. 4995

2

)

+ 0. 0005 = 0. 75025

which give the function values as


f 3 =f(x 3 )= 0. 74925 (− 0. 75075 )= − 0. 5624994375

f 4 =f(x 4 )= 0. 75025 (− 0. 74975 )= − 0. 5624999375

Sincef 3 >f 4 , we delete (0.4995,x 3 ) nd obtain the new interval of uncertainty asa


(x 3 , 1. 0 )=( 0. 74925 , 1. 0 )
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