Write working python code using local search Genetic Algorithm with following steps

a$.$ Population Initialisation,

b$.$ Fitness Selection using roulette$$s wheel,

c$.$ Cross over by single split or two split

d$.$ Mutatation

Consider,

def manhattan$\_$distance$($point$1,$ point$2)$:

x$1,$ y$1=$ node$\_$coordinates$[$point$1]$

x$2,$ y$2=$ node$\_$coordinates$[$point$2]$

return abs$($x$1-$ x$2)+$ abs$($y$1-$ y$2)$

def generate$\_$initial$\_$population$($graph$,$ population$\_$size$)$:

initial$\_$population $=[]$

for $\_$ in range$($population$\_$size$)$:

path $=$ list$($graph$.$keys$())$

random.shuffle$($path$)$

initial$\_$population.append$($path$)$

return initial$\_$population

def calculate$\_$fitness$($path$)$:

total$\_$distance $=$ sum$($manhattan$\_$distance$($path$[$i$],$ path$[$i$+1])$ for i in range$($len$($path$)-1))$

return $1/$ total$\_$distance if total$\_$distance $>0$ else float$(\text{'}$inf$\text{'})$

From diagram, representation of different places using some short forms and graph using dictionary of them as follows:

pu: Purasawalkam

pe: Perumbakkam

v: Velachery

g: Guindy

t: Tambaram

n: Nungambakkam

graph $=\{$

$\text{'}$pu$\text{'}$: $[(\text{'}$pe$\text{'},8),(\text{'}$t$\text{'},9)],$

$\text{'}$pe$\text{'}$: $[(\text{'}$pu$\text{'},8),(\text{'}$t$\text{'},11),(\text{'}$v$\text{'},6),(\text{'}$g$\text{'},7)],$

$\text{'}$v$\text{'}$: $[(\text{'}$g$\text{'},14),(\text{'}$pe$\text{'},6)],$

$\text{'}$g$\text{'}$: $[(\text{'}$pe$\text{'},7),(\text{'}$t$\text{'},10),(\text{'}$n$\text{'},12),(\text{'}$v$\text{'},14)],$

$\text{'}$n$\text{'}$: $[(\text{'}$g$\text{'},12),(\text{'}$t$\text{'},15)],$

$\text{'}$t$\text{'}$: $[(\text{'}$n$\text{'},15),(\text{'}$g$\text{'},10),(\text{'}$pe$\text{'},11),(\text{'}$pu$\text{'},9)]$

$\}$

node$\_$coordinates $=\{$

$\text{'}$pu$\text{'}$: $(0,0),$

$\text{'}$pe$\text{'}$: $(1,1),$

$\text{'}$t$\text{'}$: $(2,2),$

$\text{'}$v$\text{'}$: $(3,3),$

$\text{'}$g$\text{'}$: $(4,4),$

$\text{'}$n$\text{'}$: $(5,5)$

$\}$