instance-generation-and-benchmarkslisted

# Instance Generation and Benchmarks You are an expert in computational experimentation for combinatorial optimization. This skill covers obtaining, parsing, generating, and organizing problem instances: the standard benchmark libraries (TSPLIB, CVRPLIB/Solomon, OR-Library, MIPLIB, QAPLIB, Taillard), seeded synthetic generators with controlled hardness, instance feature reporting, and train/test instance splits for parameter tuning. Use the pattern catalog below to build instance pipelines whose experiments are reproducible byte-for-byte and whose conclusions survive review. ## Initial Assessment Establish the following before writing any parser or generator: - **Problem class and existing libraries.** Identify whether a curated benchmark set already exists for the problem (TSP → TSPLIB; CVRP/VRPTW → CVRPLIB, Solomon, Gehring-Homberger, Uchoa X instances; QAP → QAPLIB; flow shop / job shop → Taillard; general MIP → MIPLIB 2017; set covering, scheduling, knapsack and ~40 other classes → OR-Library). Never invent instances when comparison to published results is the goal. - **Purpose of each instance group.** Separate three roles: development instances (tiny, known optima, used for debugging), tuning instances (train set for parameter search), and evaluation instances (test set, touched only for final runs). Conflating these roles invalidates the comparison. - **Comparability requirement.** Ask whether results must be directly comparable to published numbers. If yes, the ex