  The growing complexity of real-world systems necessitates interdisciplinary
solutions to confront myriad challenges in modeling, analysis, management, and
control. To meet these demands, the parallel systems method rooted in
Artificial systems, Computational experiments, and Parallel execution (ACP)
approach has been developed. The method cultivates a cycle, termed parallel
intelligence, which iteratively creates data, acquires knowledge, and refines
the actual system. Over the past two decades, the parallel systems method has
continuously woven advanced knowledge and technologies from various
disciplines, offering versatile interdisciplinary solutions for complex systems
across diverse fields. This review explores the origins and fundamental
concepts of the parallel systems method, showcasing its accomplishments as a
diverse array of parallel technologies and applications, while also
prognosticating potential challenges. We posit that this method will
considerably augment sustainable development while enhancing interdisciplinary
communication and cooperation.
