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Applied Computational Intelligence and Soft Computing
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Special Issues
Applied Computational Intelligence and Soft Computing
/
2011
/
Article
/
Tab 5
/
Research Article
Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems
Table 5
Performance comparison between PSOSA, Sid.GA, Hybrid and HPSO-SA for benchmark functions [
9
].
𝐹
𝑢
𝑛
𝑐
𝑡
𝑖
𝑜
𝑛
𝐷
𝑖
𝑚
𝑒
𝑛
𝑠
𝑖
𝑜
𝑛
𝑃
𝑆
𝑂
𝑆
𝐴
𝑆
𝑡
𝑑
.
𝐺
𝐴
𝐻
𝑦
𝑏
𝑟
𝑖
𝑑
HPSO-SA
Sphere
1
0
0
±
0
2
.
4
3
𝑒
−
0
4
±
1
.
1
4
𝑒
−
0
5
2
.
4
2
𝑒
−
0
4
±
2
.
1
7
𝑒
−
0
5
0
±
0
2
0
0
±
0
0
.
0
0
1
4
5
±
6
.
2
2
𝑒
−
0
5
0
.
0
0
2
1
2
±
2
.
7
5
𝑒
−
0
4
0
±
0
3
0
0
±
0
0
.
0
0
4
4
2
±
1
.
7
8
𝑒
−
0
4
0
.
0
1
2
0
3
±
6
.
3
3
𝑒
−
0
4
0
±
0
Rastrigin
1
0
0
±
0
3
.
1
6
6
7
±
0
.
2
2
3
7
3
.
0
5
9
9
±
0
.
1
5
3
5
0
±
0
2
0
0
±
0
1
6
.
8
7
3
2
±
0
.
6
0
0
7
1
1
.
6
5
9
0
±
0
.
3
6
0
2
0
±
0
2
0
0
±
0
4
9
.
3
2
1
2
±
1
.
1
2
0
4
2
7
.
8
1
1
9
±
0
.
8
0
5
9
0
±
0
Griewank
1
0
0
±
0
2
8
3
.
2
5
1
±
1
.
8
1
2
0
.
0
9
0
7
8
±
0
.
0
3
3
0
6
0
±
0
2
0
0
±
0
6
1
1
.
2
6
6
±
3
.
5
7
2
0
.
0
0
4
5
9
±
0
.
0
1
2
0
9
0
±
0
3
0
0
±
0
8
8
9
.
5
3
7
±
3
.
9
3
9
0
.
0
9
9
1
1
±
0
.
0
0
1
0
6
0
±
0
Rosenbrock
1
0
0
.
1
7
8
5
6
±
1
.
2
5
9
8
8
1
0
9
.
8
1
0
±
6
.
2
1
2
4
3
.
5
2
1
±
1
6
.
0
4
7
0
.
1
4
6
±
0
.
2
2
4
1
9
3
2
0
0
.
0
0
0
4
3
±
0
.
0
0
1
1
1
1
4
6
.
9
1
2
±
1
0
.
9
5
1
1
6
9
.
1
1
2
±
2
1
.
5
3
5
0
.
2
4
6
8
9
7
±
0
.
2
3
1
9
8
2
3
0
0
.
5
7
4
3
1
±
4
.
0
5
9
7
6
1
9
9
.
7
3
0
±
1
6
.
2
8
5
1
8
7
.
0
3
3
±
2
2
.
9
6
0
0
.
4
3
9
1
4
9
±
0
.
3
0
4
3
4
7
