Sliced Particle Swarm Optimization (SPSO); A Computationally Efficient Optimization Technique

被引:1
作者
Garg, Harish [1 ]
Pattnaik, S. S. [1 ]
Devi, Swapna [1 ]
Bakwad, K. M. [1 ]
Panigrahi, B. K. [2 ]
Das, S. K. [3 ]
机构
[1] Natl Inst Tech Teachers Training & Res, Dept ETV & ECE, Sector 26, Chandigarh 160019, India
[2] Indian Inst Technol, Delhi, India
[3] Kansas State Univ, Manhattan, KS 66506 USA
来源
2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009) | 2009年
关键词
Sliced Particle Swarm Optimization (SPSO); momentum factor (MC); Sliced best (S-best);
D O I
10.1109/NABIC.2009.5393601
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new Optimization Technique named as Sliced Particle Swarm Optimization (SPSO) is proposed. It introduces the slicing of search space into rectangular slices. It gives complete solution in terms of reduction in the computational cost and tracking minutely each sliced search space. It introduces the momentum factor which restricts the particle in a sliced search space. Linearly decreasing inertia weight is applied throughout the computation process which balances between global exploration and local exploitation. The proposed algorithm is tested on three benchmark functions and the results are promising.
引用
收藏
页码:61 / +
页数:2
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