Page 13 - Steel Tech India eMagazine Volume October 2020
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81. Ŗ 01 Ŗ 1EVQDGT
data sGVU YJGTG UQOG CTG SWCPVKVCVKXG YJKNG VJG TGUV 5[PVJGUK\KPI VJG RTKQTKV[ XGEVQTU FGVGTOKPGF KP VJG
are only qualitative which probably can be expressed CDQXG UVGRU VQ FGVGTOKPG VJG ſPCN UEQTG HQT VJG
NKPIWKUVKECNN[ QT VJTQWIJ XCIWG GZRTGUUKQPU 5QOG QH decision choices
VJGUG CTG 2TKQTKV[ TCPMKPI QH VJG FGEKUKQP CNVGTPCVKXGU CPF
Ŗ #*2 CPF (#*2 Ō #PCN[VKE *KGTCTEJ[ 2TQEGUU (W\\[ KFGPVKH[KPI VJG VQR TCPMKPI FGEKUKQP +V OWUV DG PQVGF
Analytic Hierarchy Process VJCV DGECWUG QH KPXQNXGOGPV QH UWDLGEVKXG LWFIOGPVU
Ŗ 5#9 Ō 5KORNG #FFKVKXG 9GKIJVKPI VJGTG OC[ DG UQOG KPEQPUKUVGPEKGU KP VJG U[UVGO
5KPEG VJG SWCNKV[ QH VJG FGEKUKQP FGRGPFU QP VJG
Ŗ #02 Ō #PCN[VKE 0GVYQTM 2TQEGUU
EQPUKUVGPE[ QH VJG LWFIOGPV FWTKPI VJG EQORCTKUQP
Ŗ 6125+5 Ō 6GEJPKSWGU HQT 1TFGT 2TGHGTGPEG D[ GZGTEKUG OCLQT KPEQPUKUVGPE[ ECPPQV DG CNNQYGF KP
5KOKNCTKV[ VQ VJG +FGCN 5QNWVKQP
the process.
Ŗ '.'%64' Ō 'NKOKPCVKPI GV %JQKEG 6TCPUNCVKPI 6Q FGCN YKVJ VJKU RTQDNGO #*2 RTQXKFGU C OGVJQF QH
4GCNKV[ EQPUKUVGPE[ EJGEMKPI HQT CNN VJG RCKT YKUG EQORCTKUQPU
Ŗ 5/#46 Ō 5KORNG /WNVK #VVTKDWVG 4CVKPI 6GEJPKSWG YKVJ C NKOKV HQT CNNQYGF KPEQPUKUVGPE[ +H VJG NGXGN QH
'CEJ QH VJGUG RTQEGUUGU JCU KVU QYP RTQU CPF EQPU KPEQPUKUVGPE[ KU CEEGRVCDNG VJG FGEKUKQP RTQEGUU
CPF CRRNKECDKNKV[ /QUV QH VJGUG JCXG UQHVYCTG VQQNU VQ EQPVKPWGU *QYGXGT KH VJG NGXGN KU DG[QPF CEEGRVCDNG
GPCDNG NCTIG CPF EQORNGZ RTQDNGOU YKVJ NCTIG FCVC VQ NKOKV VJG LWFIOGPVU OWUV DG TGXKGYGF CPF VJG RTQEGUU
DG OCPCIGF HCUV OQTG CEEWTCVGN[ iterated.
6YQ QH UWEJ VGEJPKSWGU YJKEJ CTG XGTUCVKNG CPF JCXG Technique for order preference by similarity to
YKFGN[ TCPIG QH CRRNKECDKNKV[ CTG #PCN[VKE *KGTCTEJ[ ideal solution (TOPSIS)
Process (AHP) CPF 6GEJPKSWG HQT 1TFGT 2TGHGTGPEG 6125+5 KU /WNVK %TKVGTKC &GEKUKQP #PCN[UKU /%&#
D[ 5KOKNCTKV[ VQ +FGCN 5QNWVKQP (TOPSIS). The article will OGVJQF YJKEJ KFGPVKſGU VJG CNVGTPCVKXG VJCV KU CV ENQUGUV
VQWEJ WRQP VJGUG VYQ RTQEGUUGU DTKGƀ[ IGQOGVTKECN 'WENKFGCP FKUVCPEG HTQO VJG RQUKVKXG
Analytic Hierarchy Process (AHP) KFGCN UQNWVKQP 2+5 CPF HCTVJGUV HTQO VJG PGICVKXG
#*2 KU YKFGN[ WUGF KP UQNXKPI XCTKQWU EQORNGZ KFGCN UQNWVKQP +V YCU QTKIKPCNN[ FGXGNQRGF D[ %JKPI .CK
OWNVKRNG ETKVGTKC FGEKUKQP RTQDNGOU YKVJ QDLGEVKXG CPF *YCPI CPF ;QQP KP YKVJ HWTVJGT FGXGNQROGPVU
UWDLGEVKXG ETKVGTKC &GXGNQRGF D[ 6JQOCU . 5CCV[ KP D[ ;QQP KP CPF *YCPI .CK CPF .KW KP
VJG U YJQ CNUQ RCTVPGTGF YKVJ 'TPGUV (QTOCP VQ 9KMKRGFKC
FGXGNQR 'ZRGTV %JQKEG KP VJG RTQEGUU JCU DGGP A Euclidean distance is the shortest distance in space
GZVGPUKXGN[ UVWFKGF CPF TGſPGF UKPEG VJGP EQPPGEVKPI VYQ RQKPVU LQKPGF D[ C UVTCKIJV NKPG 6JGTGHQTG
6JG DCUKE RTQEGUU UVGRU QH #*2 CTG CU WPFGT KP C VYQ FKOGPUKQPCN URCEG KV KU VJG FKCIQPCN ECNEWNCVGF
CU VJG USWCTG TQQV QH VJG RGTRGPFKEWNCT CPF DCUG (QT
$TGCMKPI FQYP VJG EQORNGZ FGEKUKQP RTQDNGO KPVQ C VJTGG FKOGPUKQPCN URCEG CICKP KV YKNN DG ECNEWNCVGF
KVU EQORQPGPV RCTVU VJCV KPENWFG XCTKQWU ETKVGTKC VJG UCOG YC[ HQT CNN VJG VJTGG FKOGPUKQPU (QNNQYKPI
and decision choices
KNNWUVTCVKQPU UJCNN ENCTKH[ VJG OGVJQF QH ECNEWNCVKPI VJG
#TTCPIKPI VJGUG EQORQPGPVU QT ETKVGTKC KPVQ C Euclidean distances between two points in two and
JKGTCTEJKE QTFGT KP C 9$5 NKMG VQR FQYP UVTWEVWTG VJTGG FKOGPUKQPCN URCEGU
YKVJ VJG QXGTCNN IQCN CV VJG VQR VJG OGVJQFQNQI[ ECP
UWUVCKP OCP[ UWEJ JKGTCTEJKECN NGXGNU 6JG HQNNQYKPI ſIWTGU KNNWUVTCVGU VJG EQPEGRV
#UUKIPKPI PWOGTKECN XCNWGU VQ UWDLGEVKXG LWFIOGPVU
QP VJG TGNCVKXG KORQTVCPEG QT RTKQTKV[ QH GCEJ
ETKVGTKC CPF FGEKUKQP CNVGTPCVKXG +PFKECVKPI TGNCVKXG
RTGHGTGPEG QH FGEKUKQP CNVGTPCVKXGU YKVJ TGURGEV VQ
each criteria
2GTHQTOKPI RCKTYKUG EQORCTKUQP QH VJG ETKVGTKC CPF
FGVGTOKPKPI VJG TCVKQ UECNGU KP VJG HQTO QH C XGEVQT
%QPUKUVGPE[ EJGEMKPI
2GTHQTOKPI RCKTYKUG EQORCTKUQP QH VJG FGEKUKQP
EJQKEGU HQT GCEJ ETKVGTKC CPF FGVGTOKPKPI VJG
TCVKQ UECNGU KP VJG HQTO QH C XGEVQT HQNNQYGF D[
EQPUKUVGPE[ EJGEMKPI Fig. 2: Euclidean Distance – 2D space
STEEL TECH 11
