Information Technology Reference
In-Depth Information
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Algorithm Framework:
EINET-TSP Algorithm
Initialization
Create the initial population of
Net
.
Main Phase
do while
(End Condition)
Anity evaluation:
for
Ab
i
in
Net
do
1
aff
(
Ab
i
)=
k−
1
j
=1
d
j,j
+1
(
Ab
i
)+
d
k,
1
(
Ab
i
)
end for
Find
Ab
m
Difference evaluation:
for
Ab
i
in
Net
do
f
diff
(
Ab
i
)
max(
f
diff
)(
.
)
diff
(
Ab
i
)=
end for
Hormonal regulation:
for
Ab
i
in
Net
do
H
(
Ab
i
)=
1
90
(
atan
(2
∗
diff
(
Ab
i
)
−
1) + 45)
if
rand(0,1)
<H
(
Ab
i
)
then
Remove
Ab
i
else
if
rand(0,1)
<diff
(
Ab
i
)
then
Swap some city values (
c
j
|Ab
i
) randomly.
end if
end if
end for
Create new antibodies randomly to keep the population size of
Net
.
Antibody learning:
for
Ab
i
in
Net
do
Copy a segment in random position and add it to the end of
Ab
i
.
Delete city values (
c
j
|
Ab
i
), which are same as the values in the segment,
from
Ab
i
.
end for
Enzyme reaction:
for
Ab
i
in
Net
do
” Insert Optimal Method for
Ab
i
”
used
end for
end do
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