A Systematic Review of Wind Driven Optimization Algorithms and Their Variants

Abstract

Wind Driven Optimization (WDO) Algorithm is a novel metaheuristic algorithm inspired by the continuous flow of air resulting from differences in air pressure until the air reaches a state of pressure balance. Owing to its simple structure, few parameters, intuitive nature, and straightforward programming, WDO has garnered increasing attention from scholars since its inception. WDO’s novelty lies in its utilization of aerodynamic principles to orchestrate the search process, WDO draws on the dynamics of wind and atmospheric pressure differences to propel the search for optimal solutions. However, WDO has limitations such as sensitivity to algorithm parameters and premature convergence. Consequently, various WDO variants have been proposed to overcome the limitations of the original WDO. To identify potential avenues for further research and to develop WDO for future investigation. This article systematically reviews WDO and its variants from multiple perspectives. Initially, the principle of WDO is outlined. Subsequently, the impact of modifications to the WDO on its overall effectiveness is investigated. Furthermore, the distinctive characteristics of WDO variants and their practical applications are analyzed. Moreover, the conclusions of the review are summarized, and future research directions for WDO variants and their applications are described.

Keywords

• Wind driven optimization
• metaheuristic algorithm
• optimization
• convergence
• algorithm