multiObjective_GA
¶
Module Contents¶
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class
My_OMOPSO
(problem, epsilons, **kwargs)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.algorithms.OMOPSO
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class
MyConvergence
(*args, **kwargs)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.convergence.InterfaceConvergence
,optimeed.optimize.optiAlgorithms.platypus.core.Archive
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conv
:EvolutionaryConvergence¶
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class
MyProblem
(theOptimizationVariables, nbr_objectives, nbr_constraints, evaluationFunction)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.core.Problem
Automatically sets the optimization problem
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class
MyGenerator
(initialVectorGuess)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.Generator
Population generator to insert initial individual
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class
MyTerminationCondition
(maxTime)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.core.TerminationCondition
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class
MyMapEvaluator
(callback_on_evaluation)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.evaluator.Evaluator
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class
MyMultiprocessEvaluator
(callback_on_evaluation, numberOfCores)[source]¶ Bases:
optimeed.optimize.optiAlgorithms.platypus.evaluator.Evaluator
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class
MultiObjective_GA
[source]¶ Bases:
optimeed.optimize.optiAlgorithms.algorithmInterface.AlgorithmInterface
,optimeed.core.Option_class
Based on Platypus Library. Workflow: Define what to optimize and which function to call with a
Problem
Define the initial population with aGenerator
Define the algorithm. As options, define how to evaluate the elements with aEvaluator
, i.e., for multiprocessing. Define what is the termination condition of the algorithm withTerminationCondition
. Here, termination condition is a maximum time.-
DIVISION_OUTER
= 0¶
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OPTI_ALGORITHM
= 1¶
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NUMBER_OF_CORES
= 2¶
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