Config

BenchmarkConfig(n_hubs, n_nodes_range, n_clients_range, methods, random_nodes=True, random_n_clients_route=False, alpha=0.7, min_budget_factor=0.2, max_budget_factor=5.0, time_limit=3600, mip_gap=0.0001, int_feas_tol=1e-09, benchmark_type='n_nodes', file_name='benchmark_results', output_dir='benchmark_results', seed_dict=(lambda: {run: run for run in (range(1, 11))})(), n_runs=10, scaling=True, scaling_factor=1000) dataclass

Benchmark job configuration.

Holds everything needed to describe a single benchmark queue entry: what ranges to sweep, which methods to run, and how results are saved.