Exemplo n.º 1
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 def test_maxsat_par_alns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "maxsat-adv1.cnf"
     settings.alg = 'par_alns'
     settings.mh_titer = 600
     solution = run_optimization('MAXSAT',
                                 MAXSATInstance,
                                 MAXSATSolution,
                                 embedded=True)
Exemplo n.º 2
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 def test_vertex_cover_gvns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "frb40-19-1.mis"
     settings.alg = 'gvns'
     settings.mh_titer = 100
     solution = run_optimization('Vertex Cover',
                                 VertexCoverInstance,
                                 VertexCoverSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 726)
Exemplo n.º 3
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 def test_qap_gvns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + 'bur26a.dat'
     settings.alg = 'gvns'
     settings.mh_titer = 1000
     solution = run_optimization('QAP',
                                 QAPInstance,
                                 QAPSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 5426670)
Exemplo n.º 4
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 def test_mkp_gvns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "mknapcb5-01.txt"
     settings.alg = 'gvns'
     settings.mh_titer = 70
     solution = run_optimization('MKP',
                                 MKPInstance,
                                 MKPSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 55610)
Exemplo n.º 5
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 def test_misp_pbig(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "frb40-19-1.mis"
     settings.alg = 'pbig'
     settings.mh_titer = 500
     solution = run_optimization('MISP',
                                 MISPInstance,
                                 MISPSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 32)
Exemplo n.º 6
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 def test_graph_coloring_gvns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "fpsol2.i.1.col"
     settings.alg = 'gvns'
     settings.mh_titer = 500
     solution = run_optimization('Graph Coloring',
                                 GCInstance,
                                 GCSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 1634)
Exemplo n.º 7
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 def test_tsp_ssga(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "xqf131.tsp"
     settings.alg = 'ssga'
     settings.mh_titer = 500
     solution = run_optimization('TSP',
                                 TSPInstance,
                                 TSPSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 1376)
Exemplo n.º 8
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 def test_maxsat_gvns(self):
     seed_random_generators(42)
     settings.inst_file = data_dir + "maxsat-adv1.cnf"
     settings.alg = 'gvns'
     settings.mh_titer = 100
     solution = run_optimization('MAXSAT',
                                 MAXSATInstance,
                                 MAXSATSolution,
                                 embedded=True)
     self.assertEqual(solution.obj(), 769)
Exemplo n.º 9
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def run_algorithm_visualisation(config: Configuration):
    settings.mh_out = sum_log_vis_path
    settings.mh_log = iter_log_vis_path
    settings.mh_log_step = step_log_path 
    init_logger()

    settings.seed =  config.seed
    seed_random_generators()

    solution = run_algorithm(config,True)
    return get_log_data(config.problem.name.lower(), config.algorithm.name.lower()), solution.inst
Exemplo n.º 10
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def run_algorithm_comparison(config: Configuration):
    settings.mh_out = sum_log_path
    settings.mh_log = iter_log_path
    settings.mh_log_step = 'None'
    init_logger()
    settings.seed =  config.seed
    seed_random_generators()

    for i in range(config.runs):
        _ = run_algorithm(config)
    log_df = read_iter_log(config.name)
    summary = read_sum_log()

    return log_df, summary