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.

翻译：现实世界系统日益增长的复杂性要求跨学科解决方案，以应对建模、分析、管理与控制中的诸多挑战。为满足这些需求，基于人工系统、计算实验和平行执行（ACP）方法的平行系统方法应运而生。该方法培育了一种称为平行智能的循环机制，通过迭代创造数据、获取知识并优化实际系统。过去二十年间，平行系统方法不断融合各学科的前沿知识与技术，为不同领域的复杂系统提供了多功能的跨学科解决方案。本综述探讨了平行系统方法的起源与基本概念，展示了其作为多样化平行技术与应用所取得的成就，同时预测了潜在挑战。我们认为，该方法将在显著增强可持续发展的同时，促进跨学科交流与合作。