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optimization: Chemotaxis, Swarming, Reproduction and Elimination-dispersal. The
variables that used in the formula are explained in following.
j index for the chemotactic step
k index for reproduction step
l index of the elimination-dispersal step
p dimension of the search space
S total number of bacteria in the population
:
c N the number of chemotactic steps
:
s N the swimming length
:
N
the number of reproduction steps
re
N
:
the number of elimination-dispersal events
ed
ed P elimination-dispersal probability
:
:
( iC the size of step taken in the random location specified by the tumble
Chemotaxis: This simulates the movement of E.coli bacteria through swimming
and tumbling via flagella. Swim means the bacterial cells move in the same direction.
Tumble means the bacterial cells move in a random direction. The bacterial cells
alternate between swim and tumble for the entire lifetime. The tumble movement is
formulated as follow:
)
i
i
ʸ
(
j
+
1
k
,
l
)
=
ʸ
(
j
,
k
,
l
)
+
C
(
i
)
ˆ
(
j
)
(3)
i
th
th
ʸ
(
j
,
k
,
l
)
denotes the current position of the
i
individual at the
j
chemotaxis
th
th
step,
k
reproduction step and
l
elimination-dispersal events.
is a random
ˆ
( j
)
th
direction angle of the
j
chemotaxis step.
θ i
i
If the cost at
ʸ
(
j
+
1
k
,
l
)
is better than the cost at
(
j
,
k
,
l
)
, the bacterium will
swim another step of size
( C in the same direction as the tumble movement did,
otherwise it is allowed to tumble in a random direction
)
. The process is repeated
until the number of maximum swimming length N is reached.
Swarming: Cell-released attractants are used to signal other cells that they should
swarm together. The cell also repels a nearby cell in the sense that it consumes nearby
nutrients and it is not physically possible to have two cells at the same locations. Thus
all cells will have a cell to cell attraction via attractant and cell to cell repulsion via
repellant. The cell to cell signaling in E.coli swarm is representing as formula (4):
ʸ
( j
)
J
(
ʸ
,
p
(
j
,
k
,
l
))
=
cc
S
S
p
i
i
m
2
J
(
ʸ
,
ʸ
(
j
,
k
,
l
)
=
[
d
exp(
w
(
ʸ
ʸ
)
)]
+
cc
attrac
tan
t
attrac
tan
t
m
(4)
i
=
1
i
=
1
m
=
1
S
p
i
m
2
[
h
exp(
w
(
ʸ
ʸ
)
)]
repellant
repellant
m
i
=
1
m
=
1
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