Feature/mixed solution (#73)

* Working on implementing a IntegerFloatSolution class * Add unit test cases for class IntegerFloatProblem * Add class NMMin * Add class IntegerFloatSBXCrossover * Add test cases for SBXCrossover * Still working on implementing an approach for the IntegerFloatSolution class * Add user defined exceptiones in file checking.py * Working on the implementation of class CompositeSolution * Workon on class CompositeSolution * Class CompositeMutation implemented and tested * Fix a bug in class Neighborhood * Class CompositeCrossover implemented and tested * Add class * Add class * Rename file * Add problem ZDT1Modified * Add examples with NSGA-II * Add NSGA-II examples * Optimize imports * Minor changes * Changes on attribute name Co-authored-by: Yebisu <[email protected]>
jMetal · Feb 17, 2020 · 8c0a6cf · 8c0a6cf
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diff --git a/README.md b/README.md
@@ -68,7 +68,7 @@ algorithm = NSGAII(
     offspring_population_size=100,
     mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
     crossover=SBXCrossover(probability=1.0, distribution_index=20),
-    termination_criterion=StoppingByEvaluations(max=25000)
+    termination_criterion=StoppingByEvaluations(max_evaluations=25000)
 )
 
 algorithm.run()
@@ -99,7 +99,7 @@ plot_front.plot(front, label='NSGAII-ZDT1', filename='NSGAII-ZDT1', format='png'
 <img src=docs/source/_static/NSGAII-ZDT1.png width=450 alt="Pareto front approximation">
 
 ## Features
-The current release of jMetalPy (v1.5.3) contains the following components:
+The current release of jMetalPy (v1.5.4) contains the following components:
 
 * Algorithms: local search, genetic algorithm, evolution strategy, simulated annealing, random search, NSGA-II, NSGA-III, SMPSO, OMOPSO, MOEA/D, MOEA/D-DRA, MOEA/D-IEpsilon, GDE3, SPEA2, HYPE, IBEA. Preference articulation-based algorithms (G-NSGA-II, G-GDE3, G-SPEA2, SMPSO/RP); Dynamic versions of NSGA-II, SMPSO, and GDE3.
 * Parallel computing based on Apache Spark and Dask.

diff --git a/examples/experiment/comparison.py b/examples/experiment/comparison.py
@@ -24,7 +24,7 @@ def configure_experiment(problems: dict, n_run: int):
                         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables,
                                                     distribution_index=20),
                         crossover=SBXCrossover(probability=1.0, distribution_index=20),
-                        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+                        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
                     ),
                     algorithm_tag='NSGAII',
                     problem_tag=problem_tag,
@@ -38,7 +38,7 @@ def configure_experiment(problems: dict, n_run: int):
                         population_size=100,
                         cr=0.5,
                         f=0.5,
-                        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+                        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
                     ),
                     algorithm_tag='GDE3',
                     problem_tag=problem_tag,
@@ -53,7 +53,7 @@ def configure_experiment(problems: dict, n_run: int):
                         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables,
                                                     distribution_index=20),
                         leaders=CrowdingDistanceArchive(100),
-                        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+                        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
                     ),
                     algorithm_tag='SMPSO',
                     problem_tag=problem_tag,

diff --git a/examples/multiobjective/gde3/dynamic_gde3.py b/examples/multiobjective/gde3/dynamic_gde3.py
@@ -16,7 +16,7 @@
         population_size=100,
         cr=0.5,
         f=0.5,
-        termination_criterion=StoppingByEvaluations(max=500)
+        termination_criterion=StoppingByEvaluations(max_evaluations=500)
     )
 
     algorithm.observable.register(observer=PlotFrontToFileObserver('dynamic_front_vis'))

diff --git a/examples/multiobjective/gde3/gde3_spark_evaluator.py b/examples/multiobjective/gde3/gde3_spark_evaluator.py
@@ -1,5 +1,5 @@
-from examples.multiobjective.zdt1_modified import ZDT1Modified
 from jmetal.algorithm.multiobjective.gde3 import GDE3
+from jmetal.problem.multiobjective.zdt import ZDT1Modified
 from jmetal.util.evaluator import SparkEvaluator
 from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
 from jmetal.util.termination_criterion import StoppingByEvaluations
@@ -12,7 +12,7 @@
         population_size=10,
         cr=0.5,
         f=0.5,
-        termination_criterion=StoppingByEvaluations(max=100),
+        termination_criterion=StoppingByEvaluations(max_evaluations=100),
         population_evaluator=SparkEvaluator()
     )
 

diff --git a/examples/multiobjective/gde3/ggde3_zdt2.py b/examples/multiobjective/gde3/ggde3_zdt2.py
@@ -16,7 +16,7 @@
         population_size=100,
         cr=0.5,
         f=0.5,
-        termination_criterion=StoppingByEvaluations(max=max_evaluations),
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations),
         dominance_comparator=GDominanceComparator(reference_point)
     )
 

diff --git a/examples/multiobjective/ibea/ibea_zdt1.py b/examples/multiobjective/ibea/ibea_zdt1.py
@@ -15,7 +15,7 @@
         offspring_population_size=100,
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
-        termination_criterion=StoppingByEvaluations(25000)
+        termination_criterion=StoppingByEvaluations(max_evaluations=25000)
     )
 
     algorithm.run()

diff --git a/examples/multiobjective/mocell/mocell_zdt1.py b/examples/multiobjective/mocell/mocell_zdt1.py
@@ -1,12 +1,10 @@
 from jmetal.util.solution_list import print_function_values_to_file, print_variables_to_file
 
 from jmetal.algorithm.multiobjective.mocell import MOCell
-from jmetal.lab.visualization import Plot
 from jmetal.operator import SBXCrossover, PolynomialMutation
 from jmetal.problem import ZDT1
 from jmetal.util.archive import CrowdingDistanceArchive
 from jmetal.util.neighborhood import C9
-from jmetal.util.observer import ProgressBarObserver
 from jmetal.util.solution import read_solutions
 from jmetal.util.termination_criterion import StoppingByEvaluations
 
@@ -22,7 +20,7 @@
         archive=CrowdingDistanceArchive(100),
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/examples/multiobjective/moead/moead_dtlz2.py b/examples/multiobjective/moead/moead_dtlz2.py
@@ -21,7 +21,7 @@
         neighbourhood_selection_probability=0.9,
         max_number_of_replaced_solutions=2,
         weight_files_path='resources/MOEAD_weights',
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/examples/multiobjective/moead/moead_iepsilon_lircmop1.py b/examples/multiobjective/moead/moead_iepsilon_lircmop1.py
@@ -22,7 +22,7 @@
         neighbourhood_selection_probability=0.9,
         max_number_of_replaced_solutions=2,
         weight_files_path='resources/MOEAD_weights',
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/examples/multiobjective/moead/moead_lz09.py b/examples/multiobjective/moead/moead_lz09.py
@@ -22,7 +22,7 @@
         neighbourhood_selection_probability=0.9,
         max_number_of_replaced_solutions=2,
         weight_files_path='resources/MOEAD_weights',
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/examples/multiobjective/moead/moeaddra_lz09.py b/examples/multiobjective/moead/moeaddra_lz09.py
@@ -21,7 +21,7 @@
         neighbourhood_selection_probability=0.9,
         max_number_of_replaced_solutions=2,
         weight_files_path='resources/MOEAD_weights',
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/...ltiobjective/nsgaii/distributed_nsgaii.py → ...ve/nsgaii/distributed_nsgaii_with_dask.py b/...ltiobjective/nsgaii/distributed_nsgaii.py → ...ve/nsgaii/distributed_nsgaii_with_dask.py
@@ -1,11 +1,15 @@
 from dask.distributed import Client
 from distributed import LocalCluster
 
-from examples.multiobjective.zdt1_modified import ZDT1Modified
 from jmetal.algorithm.multiobjective.nsgaii import DistributedNSGAII
 from jmetal.operator import PolynomialMutation, SBXCrossover
+from jmetal.problem.multiobjective.zdt import ZDT1Modified
 from jmetal.util.termination_criterion import StoppingByEvaluations
 
+""" 
+Distributed (asynchronous) version of NSGA-II using Dask.
+"""
+
 if __name__ == '__main__':
     problem = ZDT1Modified()
 
@@ -23,7 +27,7 @@
         population_size=100,
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
-        termination_criterion=StoppingByEvaluations(max=max_evaluations),
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations),
         number_of_cores=ncores,
         client=client
     )

diff --git a/...objective/nsgaii/nsgaii_dask_evaluator.py → ...distributed_nsgaii_with_dask_evaluator.py b/...objective/nsgaii/nsgaii_dask_evaluator.py → ...distributed_nsgaii_with_dask_evaluator.py
@@ -1,10 +1,13 @@
-from examples.multiobjective.zdt1_modified import ZDT1Modified
 from jmetal.algorithm.multiobjective.nsgaii import NSGAII
 from jmetal.operator import SBXCrossover, PolynomialMutation
+from jmetal.problem.multiobjective.zdt import ZDT1Modified
 from jmetal.util.evaluator import DaskEvaluator
 from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
 from jmetal.util.termination_criterion import StoppingByEvaluations
 
+""" 
+Distributed (synchronous) version of NSGA-II using Dask.
+"""
 if __name__ == '__main__':
     problem = ZDT1Modified()
 
@@ -17,7 +20,7 @@
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
         population_evaluator=DaskEvaluator(),
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()
@@ -31,4 +34,3 @@
     print(f'Problem: ${problem.get_name()}')
     print(f'Computing time: ${algorithm.total_computing_time}')
 
-
diff --git a/...bjective/nsgaii/nsgaii_spark_evaluator.py → ...istributed_nsgaii_with_spark_evaluator.py b/...bjective/nsgaii/nsgaii_spark_evaluator.py → ...istributed_nsgaii_with_spark_evaluator.py
@@ -1,10 +1,14 @@
-from examples.multiobjective.zdt1_modified import ZDT1Modified
 from jmetal.algorithm.multiobjective.nsgaii import NSGAII
 from jmetal.operator import SBXCrossover, PolynomialMutation
+from jmetal.problem.multiobjective.zdt import ZDT1Modified
 from jmetal.util.evaluator import SparkEvaluator
 from jmetal.util.solution import print_function_values_to_file, print_variables_to_file
 from jmetal.util.termination_criterion import StoppingByEvaluations
 
+""" 
+Distributed (synchronous) version of NSGA-II using Apache Spark.
+"""
+
 if __name__ == '__main__':
     problem = ZDT1Modified()
 
@@ -17,7 +21,7 @@
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
         population_evaluator=SparkEvaluator(),
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.run()

diff --git a/...s/multiobjective/nsgaii/dynamic_nsgaii.py → ...ive/nsgaii/dynamic_nsgaii_solving_fda2.py b/...s/multiobjective/nsgaii/dynamic_nsgaii.py → ...ive/nsgaii/dynamic_nsgaii_solving_fda2.py
@@ -19,7 +19,7 @@
         offspring_population_size=100,
         mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
         crossover=SBXCrossover(probability=1.0, distribution_index=20),
-        termination_criterion=StoppingByEvaluations(max=max_evaluations)
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
     )
 
     algorithm.observable.register(observer=PlotFrontToFileObserver('dynamic_front_vis'))

diff --git a/examples/multiobjective/nsgaii/gnsgaii_solving_zdt2_with_reference_point.py b/examples/multiobjective/nsgaii/gnsgaii_solving_zdt2_with_reference_point.py
@@ -0,0 +1,55 @@
+from jmetal.algorithm.multiobjective.nsgaii import NSGAII
+from jmetal.lab.visualization import Plot, InteractivePlot
+from jmetal.operator import SBXCrossover, PolynomialMutation
+from jmetal.problem import ZDT2
+from jmetal.util.comparator import GDominanceComparator
+from jmetal.util.observer import ProgressBarObserver, VisualizerObserver
+from jmetal.util.solution import print_function_values_to_file, print_variables_to_file, read_solutions
+from jmetal.util.termination_criterion import StoppingByEvaluations
+
+"""  
+Program to configure and run G-NSGA-II (NSGA-II with G-Dominance) to solve problem ZDT2 with 
+reference point = [0.2, 0.5].
+"""
+
+if __name__ == '__main__':
+    problem = ZDT2()
+    problem.reference_front = read_solutions(filename='resources/reference_front/ZDT2.pf')
+
+    reference_point = [0.2, 0.5]
+
+    max_evaluations = 25000
+    algorithm = NSGAII(
+        problem=problem,
+        population_size=100,
+        offspring_population_size=100,
+        mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
+        crossover=SBXCrossover(probability=1.0, distribution_index=20),
+        dominance_comparator=GDominanceComparator(reference_point),
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
+    )
+
+    algorithm.observable.register(observer=ProgressBarObserver(max=max_evaluations))
+    algorithm.observable.register(
+        observer=VisualizerObserver(reference_front=problem.reference_front, reference_point=reference_point))
+
+    algorithm.run()
+    front = algorithm.get_result()
+
+    # Plot front
+    plot_front = Plot(title='Pareto front approximation. Problem: ' + problem.get_name(),
+                      reference_front=problem.reference_front, axis_labels=problem.obj_labels)
+    plot_front.plot(front, label=algorithm.label, filename=algorithm.get_name())
+
+    # Plot interactive front
+    plot_front = InteractivePlot(title='Pareto front approximation. Problem: ' + problem.get_name(),
+                                 reference_front=problem.reference_front, axis_labels=problem.obj_labels)
+    plot_front.plot(front, label=algorithm.label, filename=algorithm.get_name())
+
+    # Save results to file
+    print_function_values_to_file(front, 'FUN.' + algorithm.label)
+    print_variables_to_file(front, 'VAR.' + algorithm.label)
+
+    print('Algorithm (continuous problem): ' + algorithm.get_name())
+    print('Problem: ' + problem.get_name())
+    print('Computing time: ' + str(algorithm.total_computing_time))
diff --git a/examples/multiobjective/nsgaii/nsgaii_defining_schaffer_problem_on_the_fly.py b/examples/multiobjective/nsgaii/nsgaii_defining_schaffer_problem_on_the_fly.py
@@ -0,0 +1,49 @@
+from jmetal.algorithm.multiobjective.nsgaii import NSGAII
+from jmetal.core.problem import OnTheFlyFloatProblem
+from jmetal.operator import SBXCrossover, PolynomialMutation
+from jmetal.util.solution import get_non_dominated_solutions, read_solutions, print_function_values_to_file, \
+    print_variables_to_file
+from jmetal.util.termination_criterion import StoppingByEvaluations
+
+"""  
+Program to  configure and run the NSGA-II algorithm configured with standard settings.
+"""
+
+if __name__ == '__main__':
+    # Defining problem Schaffer on the fly
+    def f1(x: [float]):
+        return x[0] * x[0]
+
+    def f2(x: [float]):
+        return (x[0] - 2) * (x[0] - 2)
+
+    problem = OnTheFlyFloatProblem()
+    problem \
+        .set_name('Schaffer') \
+        .add_variable(-10000.0, 10000.0) \
+        .add_function(f1) \
+        .add_function(f2)
+
+    problem.reference_front = read_solutions(filename='resources/reference_front/ZDT1.pf')
+
+    max_evaluations = 25000
+    algorithm = NSGAII(
+        problem=problem,
+        population_size=100,
+        offspring_population_size=100,
+        mutation=PolynomialMutation(probability=1.0 / problem.number_of_variables, distribution_index=20),
+        crossover=SBXCrossover(probability=1.0, distribution_index=20),
+        termination_criterion=StoppingByEvaluations(max_evaluations=max_evaluations)
+    )
+
+    algorithm.run()
+    front = get_non_dominated_solutions(algorithm.get_result())
+
+    # Save results to file
+    print_function_values_to_file(front, 'FUN.' + algorithm.label)
+    print_variables_to_file(front, 'VAR.'+ algorithm.label)
+
+    print('Algorithm (continuous problem): ' + algorithm.get_name())
+    print('Problem: ' + problem.get_name())
+    print('Computing time: ' + str(algorithm.total_computing_time))
+