Table 1 Efficiency analysis of the three initialization methods in generating valid results (\(\alpha = 0.05\)).

From: A spherical vector-based adaptive evolutionary particle swarm optimization for UAV path planning under threat conditions

Initialization

[Algorithm]

Traditional method based on CCS

[PSO]

Traditional method based on SCS

[SGWO,SWOA,SHHO,SDBO,SPSO]

Optimization method in this paper

[SAEPSO]

Environment

Max.

Min.

Mean

Std

T-test

Max.

Min.

Mean

Std

T-test

Max.

Min.

Mean

Std

T-test

Scenario 1

28

1

10

8.78

6

1

1.75

1.25

1

1

1

0.00

Scenario 2

239

2

61.9

67.09

9

1

3.05

2.39

3

1

1.35

0.59

Scenario 3

402

48

194.25

117.37

126

2

28.35

30.07

31

1

12.25

10.12

Scenario 4

625

2

183.45

162.80

5

1

1.75

1.07

O

3

1

1.5

0.69

Scenario 5

1882

22

617.2

591.06

21

1

7.95

6.13

5

1

1.9

1.12

Scenario 6

6555

7

1498.85

1637.48

50

1

13.45

14.94

8

1

2.55

2.19

  1. Bold indicates the best result among all the algorithms or methods compared in the comparative experiments.