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Simulation result shows that the two AGV task get better match after optimization,
the working time is shorted, PSO has higher efficiency and better uniformity than the
GA algorithm's task distribution.
Table 3. Simulation result comparison about PSO and GA
Optimization algorithm
iterations
AGV1
AGV2
Time/s
GA
50
1300
1454
1562
GA
100
1419
1396
1478
PSO
50
1402
1400
1474
PSO
100
1358
1352
1418
5 Conclusion
In this paper, under the premise of referencing to the literature [8], the PSO applica-
tion area is transferred, it is used in discrete space optimization, a modified POS is
came up with. After comparing with previous algorithm, a better result is obtained.
Acknowledgements. This work has been supported in part by the Tianjin City High
School Science & Technology Fund Project No. 20090704.
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