Study of Socio-inspired Metaheuristic Algorithms Through a Proposed Generic Framework

In recent years, the socio-inspired algorithms, one of the subclasses of metaheuristics, have been looked upon active in the research community. This novel subclass has been inspired by the human behavior and social activities/interactions exhibited by the individuals to improve themselves. Multiple socio-inspired algorithms have been proposed till date, and the research is still going on to map new concepts of human behavior into algorithms. This paper proposes a generic framework for socio-inspired algorithms to comprehend the working structure of these metaheuristic algorithms. Additionally, to prove the authenticity of the proposed framework, 10 recently developed (2019–2023) socio-inspired metaheuristic algorithms have been reviewed against this framework. The authors anticipate that this generic framework can be used as a benchmark to study the socio-inspired metaheuristic algorithms developed in future.