Comparisons of several variants of continuous quantum-inspired evolutionary algorithms. Issue 4 (4th July 2017)

• Record Type: Journal Article
• Authors: Mozaffari, Ahmad; Emami, Mahdi; Azad, Nasser L.; Fathi, Alireza
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 29:Issue 4(2017)
• Page Start: 869
• Page End: 909
• Publication Date: 2017-07-04
• Subjects: Quantum evolutionary algorithms -- chaos-enhanced quantum-inspired operators -- numerical optimisation -- convergence analysis -- scalability analysis; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2016.1264088
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract: In this study, an extensive numerical analysis is carried out to investigate the effects of different quantum-based operators on the performance of continuous quantum-inspired evolutionary algorithms (QEAs). In this context, different variants of quantum-inspired evolutionary operators are adopted for numerical simulations. Furthermore, some novel chaos-enhanced QEAs are proposed and their performances are evaluated through the numerical comparative study. Based on evaluating the accuracy, robustness, convergence, scalability and sensitivity to initialisation of the rival methods, it is indicated that the algorithmic structure of QEAs is prone to being combined with chaotic maps. The results demonstrate that chaotically implemented QEAs can effectively explore/exploit the solution spaces of different landscapes and dimensionality, and finally, converge to acceptable regions within the solution domain.