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arXiv · 1304.3892

An accelerated CLPSO algorithm

Muhammad Omer Bin Saeed·Muhammad Saqib Sohail·Syed Zeeshan Rizvi·Mobien Shoaib·Asrar Ul Haq Sheikh
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Abstract

The particle swarm approach provides a low complexity solution to the optimization problem among various existing heuristic algorithms. Recent advances in the algorithm resulted in improved performance at the cost of increased computational complexity, which is undesirable. Literature shows that the particle swarm optimization algorithm based on comprehensive learning provides the best complexity-performance trade-off. We show how to reduce the complexity of this algorithm further, with a slight but acceptable performance loss. This enhancement allows the application of the algorithm in time critical applications, such as, real-time tracking, equalization etc.

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Muhammad Omer Bin Saeed, Muhammad Saqib Sohail, Syed Zeeshan Rizvi, Mobien Shoaib, Asrar Ul Haq Sheikh. 2013-04-14. An accelerated CLPSO algorithm. https://arxiv.org/abs/1304.3892

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