TrEO Benchmark Suite

TrEO Benchmark Suite是由大连理工大学计算机科学与技术学院的研究团队开发的一个实用优化问题数据集，包含三个代表性问题：背包问题、平面机械臂问题和极简攻击问题。该数据集旨在通过模拟现实世界中的大规模、多样化和高速源任务实例，评估和推动转移进化优化（TrEO）算法的发展。背包问题侧重于大规模源任务实例的体积特性，平面机械臂问题结合了体积和多样性特性，而极简攻击问题则涉及体积和速度特性。通过这些问题的解决，数据集旨在促进对算法在面对多样化和复杂转移场景时性能的深入理解，为研究人员提供一个宝贵的资源，以改进和推进TrEO算法在解决实际问题中的应用。

The TrEO Benchmark Suite is a practical optimization problem dataset developed by the research team from the School of Computer Science and Technology, Dalian University of Technology. It comprises three representative problems: the knapsack problem, the planar manipulator problem, and the minimalist attack problem. This dataset is designed to evaluate and advance the development of Transferable Evolutionary Optimization (TrEO) algorithms by simulating large-scale, diverse, and high-speed real-world task instances. The knapsack problem focuses on the volume characteristics of large-scale source task instances, the planar manipulator problem combines volume and diversity characteristics, while the minimalist attack problem involves volume and speed characteristics. By solving these problems, the dataset aims to foster an in-depth understanding of algorithm performance when facing diverse and complex transfer scenarios, and provide researchers with a valuable resource to improve and advance the application of TrEO algorithms in solving real-world problems.