45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
from src import *
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from concorde.tsp import TSPSolver
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def run(show_plots=False):
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# names = [name_ for name_ in os.listdir("./problems") if "tsp" in name_]
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names = ["ch130.tsp"]
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for name in names:
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print("\n\n#############################")
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filename = f"problems/{name}"
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instance = Instance(filename)
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instance.print_info()
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if show_plots:
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instance.plot_data()
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solver = TSPSolver.from_data(
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instance.points[:, 1]*100,
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instance.points[:, 2]*100,
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norm="EUC_2D"
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)
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solution = solver.solve(verbose=False)
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tour_opt = np.copy(solution.tour)
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for method in ["random", "nearest_neighbors", "best_nn"]:
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solver = Solver_TSP(method)
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solver(instance, return_value=False)
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print(f"the total length for the solution found is {solver.found_length}",
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f"while the optimal length is {instance.best_sol}",
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f"the gap is {solver.gap} %", sep="\n")
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if show_plots:
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solver.plot_solution()
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solver.method = "optimal"
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solver.solution = np.concatenate([tour_opt, [tour_opt[0]]])
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solver.solved = True
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solver.plot_solution()
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print(solver.evaluate_solution(return_value=True))
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if __name__ == '__main__':
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run(show_plots=True)
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