Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review

Abstract Throughout the centuries, nature has been a source of inspiration, with much still to learn from and discover about. Among many others, Swarm Intelligence (SI), substantial branch Artificial Intelligence, is built on intelligent collective behavior social swarms in nature. One most popular SI paradigms, Particle Optimization algorithm (PSO), presented this work. Many changes have made PSO since its inception mid 1990s. Since their learning about technique, researchers practitioners developed new applications, derived versions, published theoretical studies potential influence various parameters aspects algorithm. Various perspectives are surveyed paper existing ongoing research, including methods, diverse application domains, open issues, future perspectives, based Systematic Review (SR) process. More specifically, analyzes research methods applications between 2017 2019 technical taxonomy picked content, hybridization, improvement, variants PSO, as well real-world categorized into: health-care, environmental, industrial, commercial, smart city, general applications. Some characteristics, accuracy, evaluation environments, proposed case study involved investigate effectiveness different Each addressed some valuable advantages unavoidable drawbacks which discussed accordingly yielded hints for addressing weaknesses those highlighting issues