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Fig. 5.
The processing flow chart of one AGV and its Petri model
Fig. 6.
Simulation interface of FMS logistics system
System optimization method is POS, which is discussed as follows.
3 Application of PSO
3.1 Description of Issue
In logistics system, there are some assignment and scheduling problems of multiple
AGVs to a number of transport-tasks, which need to be ordered by scheduling rules.
Therefore, after more than one tasks were applied and about to enter AGV waiting
queue, these tasks should be scheduled. The scheduler should reasonable and arrange-
ments for each AGV task to improve the efficiency of all. Scheduled task assigned to
each AGV's waiting queue and to be executed in turn [6].To solve this problem, Parti-
cle swarm optimization (PSO) [7] is used to optimize the proposed model above.
3.2 Algorithm Description
Assuming in a n-dimensional goal-search space, there is a group consist of N parti-
cles, of which the
i
- particle represents a n-dimensional vector
x
i
= ( x
i1
, x
i2
,…,x
in
)
,
i
= 1, 2, ..., N, and the position of each particle is a potential solution. The flight speed
of i-particle is also a n-dimensional vector, denoted as
v
i
= (v
i1
, v
i2
,…, v
in
)
. The best
location of the i-particle searched so far is recorded as p
i
=( p
i1
,p
i2
, …, p
in
), and the
best location of the entire population of particles is recorded as
p
g
= (p
g1
, p
g2
, …, p
gn
)
,
ω
is the weight. Formula (1) and (2) are often referred to as the standard equation of
PSO algorithm:
(
t
+
1
(
t
)
(
t
)
(
t
)
(
t
g
)
(
t
g
)
(1)
v
=
wv
+
c
r
(
p
−
x
)
+
c
r
(
p
−
x
)
1
1
2
2
i
i
i
i
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