Neutrosophic Optimization and its Application on Structural Designs

Page 246

X j  Rd , j  1, 2,....., n

(9.9)

X  0; s  0,1

(9.10)

where C ( X ; s) represents cost function,  i  X ; s  is the behavioural constraints and

 i  X ; s  denotes the maximum allowable value , ‘m’ and ‘n’ are the number of constraints d and design variables respectively. A given set of discrete value is expressed by R and in this

chapter objective function is taken as T

m

t 1

n 1

C  X ; s    ct  s   xntn

(9.11)

and constraint are chosen to be stress of structures as follows

 i  X ; s  n  i  s  with allowable tolerance  i0  s  for i  1,2,...., m

(9.12)

The deflection of the structure as follows 0   X ; s  n  max  s  with allowable tolerance  max s

(9.13) th

Where ct is the cost coefficient of tth side and xn is the n design variable respectively, m is 0 the number of structural element,  i and  i0  s   max  s  are the i stress , allowable stress and

th

allowable deflection respectively. To solve the SOWBP (P9.2), step 1 of 1.40 is used and let UCT  X ;s  ,UCI  X ;s  ,UCF X ;s  be the upper bounds of truth, indeterminacy , falsity function for the objective respectively and LTC  X ;s  , LIC  X ;s  , LFC  X ;s  be the lower bound of truth, indeterminacy, falsity membership

functions of objective respectively then

 

 



U CT  X ;s   max C X 1; s , C X 2 ; s ,

 

 

(9.14)



LTf  x;s   min C X 1; s , C X 2 ; s ,

(9.15)

U CF X ;s   U CT  X ;s  ,

(9.16)

LFC  X ;s   LTC  X ;s    C  X ;s  where 0   C  X ;s   U CT  X ;s   LTC  X ;s 

LIC  X ;s   LTC  X ;s  ,

(9.17) (9.18)

U CI  X ;s   LTC  X ;s   C  X ;s  where 0  C  X ;s   UCT  X ;s   LTC  X ;s 

Page 232

(9.19)


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