International Journal of Nonlinear Analysis and Applications

The application of meta-synthesis in the identification of new combined genetic algorithm methods to solve complex problems

Document Type : Research Paper

Authors

1 Department of Industrial Management, Yazd Branch, Islamic Azad University, Yazd, Iran

2 Department of Industrial Engineering, Meybod University, Meybod, Iran

Abstract

The current research aims to identify new combined genetic algorithm methods to solve complex problems. The researcher has analyzed the results and findings of the previous researchers using a systematic reviewing approach and has identified the effective factors by implementing the 7 steps of Sandelowski and Barroso’s method. Among 4320 articles, 54 articles were selected based on the CASP method. In this manner, in order to evaluate reliability and quality control, the Kappa index was used, and its value was deemed to be in high compatibility regarding the identified factors. The results of the analysis of the collected data in ATLAS TI software led to the identification of 9 categories and 33 primary codes of new combined genetic algorithm methods to solve complex problems. Based on the coding, 9 categories, and 33 initial codes were identified. The identified categories are layout design, supply network, programming, Anticipation, inventory control, information security, imaging, medical imaging and wireless network.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 15, Issue 7
July 2024
Pages 183-195
  • Receive Date: 11 March 2023
  • Revise Date: 23 June 2023
  • Accept Date: 25 June 2023