Abstract Mathematical programming solvers are software tools designed to solve real-world problems using mathematical programming algorithms. This survey explores the evolution of optimization technologies, from traditional methods such as the simplex algorithm and branch-and-bound techniques to modern advancements that are facilitated by parallel computing, GPU acceleration, and AI algorithms. We also emphasize the recent emergence of mathematical programming solvers developed by research institutes and companies headquartered in China as major players, who have achieved remarkable success in benchmarks when compared to established solvers. This article provides a comprehensive overview of the theoretical foundations, historical progress, and emerging trends in mathematical programming solvers, offering valuable insights for both researchers and practitioners in the field.
Huang et al. (Sun,) studied this question.