Title of article
The application of meta-synthesis in the identification of new combined genetic algorithm methods to solve complex problems
Author/Authors
Ebrahimi ، Mohammad Ali Department of Industrial Management - Islamic Azad University, Yazd Branch , Dehghan Dehnavi ، Hassan Department of Industrial Management - Islamic Azad University, Yazd Branch , Mirabi ، Mohammad Department of Industrial Engineering - Meybod University , Honari ، Mohammad Taghi Department of Industrial Management - Islamic Azad University, Yazd Branch , Sadeghian ، Abolfazl Department of Industrial Management - Islamic Azad University, Yazd Branch
From page
183
To page
195
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
genetic algorithm , complex problems , meta , synthesis
Journal title
International Journal of Nonlinear Analysis and Applications
Journal title
International Journal of Nonlinear Analysis and Applications
Record number
2773813
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