<p>Metaheuristic Algorithms (MAs) guide the optimization process through heuristic information to find a approximate optimal solution to the problem. In the past few years, MAs have been widely used in areas such as NP-hard problems, medical sciences, and robotics due to their flexibility, adaptability, and extensive search capabilities. As a result, more and more MAs have been proposed. Swarm Intelligence Algorithms (SIAs) are an important class of MAs, and Dandelion Optimizer (DO) is one of the novel and prominent members. This review introduces a novel population-based metaheuristic algorithm, DO, and analyzes its main features. As a novel and effective intelligent optimization algorithm, DO has been in ESI hot/highly cited paper status from July 2023 to January 2025 and has been successfully extended to the intelligent solution of different optimization problems and application areas. To review and analyze the recent progress and developmental dynamics of DO, this review paper dynamically traces a series of related research works on DO, focusing on variants of DO, such as hybridization of DO, modification of DO, chaotic DO, and multi-objective DO. In addition, this paper also focuses on the application aspects, such as testing functionalities, engineering applications, medical applications, machine learning applications, and web applications. According to studies, the highest percentage of hybridization is found in the above categories, and the area with the most applied DOs is the power system. What’s more, this review paper provides the advantages, disadvantages of DO and future research perspectives for scholars who are interested in further exploring DO.</p>