Parameters analysis of QIEA-R in convergence quality

No Thumbnail Available
Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
QIEA-R (Quantum Inspired Evolutionary Algorithm with Real Codification) was proposed for solving numerical problems obtaining better results when compared with traditional EAs, DE and PSO algorithms. It is inspired on the concept of quantum superposition in order to reduce the number of evaluations. QIEA-R has two important steps: initialization of the quantum population and updating of the quantum population. This paper analyzes these two steps and parameters related: Size of classical population, number of iterations, over some benchmark functions using statistical measurements to evaluate their importance and effect in convergence quality. The results shows the importance of quantum population size and update frequency. © 2016 IEEE.
Description
Citation
Collections