MATEC Web Conf.
Volume 100, 201713th Global Congress on Manufacturing and Management (GCMM 2016)
|Number of page(s)||3|
|Section||Part 2: Internet +, Big data and Flexible manufacturing|
|Published online||08 March 2017|
Research on Multiple Particle Swarm Algorithm Based on Analysis of Scientific Materials
School of Information Engineering, Shenyang University, Shenyang, China
* Corresponding Email: firstname.lastname@example.org
This paper proposed an improved particle swarm optimization algorithm based on analysis of scientific materials. The core thesis of MPSO (Multiple Particle Swarm Algorithm) is to improve the single population PSO to interactive multi-swarms, which is used to settle the problem of being trapped into local minima during later iterations because it is lack of diversity. The simulation results show that the convergence rate is fast and the search performance is good, and it has achieved very good results.
Key words: Swarm intelligence / particle swarm / scientific materials / bacterial foraging optimization
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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