from src import * import pandas as pd def run(show_plots=False, verbose=False): # names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_] names = ["eil76.tsp"] initializers = Solver_TSP.available_initializers.keys() improvements = Solver_TSP.available_improvements.keys() results = [] index = [] for name in names: filename = f"problems/{name}" instance = Instance(filename) if verbose: print("\n\n#############################") instance.print_info() if show_plots: instance.plot_data() for init in initializers: solver = Solver_TSP(init) for improve in improvements: solver.bind(improve) solver(instance, return_value=False, verbose=verbose) if verbose: print(f"the total length for the solution found is {solver.found_length}", f"while the optimal length is {instance.best_sol}", f"the gap is {solver.gap}%", f"the solution is found in {solver.time_to_solve} seconds", sep="\n") index.append((name, solver.name_method)) results.append([solver.found_length, instance.best_sol, solver.gap, solver.time_to_solve]) if show_plots: solver.plot_solution() if instance.exist_opt and show_plots: solver.solution = np.concatenate([instance.optimal_tour, [instance.optimal_tour[0]]]) solver.method = "optimal" solver.plot_solution() index = pd.MultiIndex.from_tuples(index, names=['problem', 'method']) return pd.DataFrame(results, index=index, columns=["tour length", "optimal solution", "gap", "time to solve"]) if __name__ == '__main__': df = run(show_plots=False, verbose=True) df.to_csv("./results.csv")