NDLI: A two-stage quantum-behaved particle swarm optimization with skipping search rule and weight to solve continuous optimization problem

Content Provider	Springer Nature Link
Author	Tang, Deyu Dong, Shoubin Cai, Xianfa Zhao, Jie
Copyright Year	2015
Abstract	Quantum-behaved particle swarm optimization (QPSO) is a recently developed heuristic method by particle swarm optimization (PSO) algorithm based on quantum mechanics, which outperforms the search ability of original PSO. But as many other PSOs, it is easy to fall into the local optima for the complex optimization problems. Therefore, we propose a two-stage quantum-behaved particle swarm optimization with a skipping search rule and a mean attractor with weight. The first stage uses quantum mechanism, and the second stage uses the particle swarm evolution method. It is shown that the improved QPSO has better performance, because of discarding the worst particles and enhancing the diversity of the population. The proposed algorithm (called ‘TSQPSO’) is tested on several benchmark functions and some real-world optimization problems and then compared with the PSO, SFLA, RQPSO and WQPSO and many other heuristic algorithms. The experiment results show that our algorithm has better performance than others.
Starting Page	2429
Ending Page	2440
Page Count	12
File Format	PDF
ISSN	09410643
Journal	Neural Computing and Applications
Volume Number	27
Issue Number	8
e-ISSN	14333058
Language	English
Publisher	Springer London
Publisher Date	2015-08-25
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Particle swarm optimization Quantum behavior Two-stage search strategy Skipping search rule Weighted mean best position Artificial Intelligence (incl. Robotics) Data Mining and Knowledge Discovery Probability and Statistics in Computer Science Computational Science and Engineering Image Processing and Computer Vision Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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