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

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 ۷ steps of Sandelowski and Barroso’s method. Among ۴۳۲۰ articles, ۵۴ 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 ۹ categories and ۳۳ primary codes of new combined genetic algorithm methods to solve complex problems. Based on the coding, ۹ categories, and ۳۳ 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