Documentation

macop

macop.algorithms

macop.algorithms.Algorithm

Abstract Algorithm class used as basic algorithm implementation with some specific initialization

macop.algorithms.mono.IteratedLocalSearch

Iterated Local Search Algorithm implementation

macop.algorithms.mono.HillClimberFirstImprovment

Hill Climber First Improvment algorithm starting from new solution and explore using neighborhood and loop over the best one obtained from neighborhood search space

macop.algorithms.mono.HillClimberBestImprovment

Hill Climber Best Improvment algorithm starting from new solution and explore using neighborhood and loop over the best one obtained from neighborhood search space

macop.algorithms.multi.MOEAD

Multi-Ojective Evolutionary Algorithm with Scalar Decomposition algorithm

macop.algorithms.multi.MOSubProblem

MOEAD sub problem algorithm class

macop.callbacks

macop.callbacks.BasicCheckpoint

Basic Checkpoint class implementation

macop.callbacks.MultiCheckpoint

Multi Checkpoint class implementation

macop.callbacks.ParetoCheckpoint

Pareto front Checkpoint class implementation

macop.callbacks.UCBCheckpoint

UCB policy Checkpoint class implementation

macop.callbacks.Callback

Abstract Checkpoint class

macop.evaluators

macop.evaluators.EvaluatorExample

Python evaluator function example

macop.operators

macop.operators.crossovers.Crossover

Abstract Crossover class

macop.operators.crossovers.RandomSplitCrossover

Crossover implementation which generated new solution by randomly splitting best solution and current solution

macop.operators.crossovers.SimpleCrossover

Crossover implementation which generated new solution by splitting at mean size best solution and current solution

macop.operators.mutators.Mutation

Abstract Mutation class

macop.operators.mutators.SimpleBinaryMutation

Mutation implementation for binary solution, swap bit randomly from solution

macop.operators.mutators.SimpleMutation

Mutation implementation for binary solution, swap two bits randomly from solution

macop.operators.policies.Policy

Abstract class which is used for applying strategy when selecting and applying operator

macop.operators.policies.RandomPolicy

Policy class implementation which is used for selecting operator randomly

macop.operators.policies.UCBPolicy

Policy class implementation which is used for selecting operator using Upper Confidence Bound

macop.operators.Operator

Abstract Operator class

macop.solution

macop.solutions.BinarySolution

Binary solution class implementation

macop.solutions.CombinatoryIntegerSolution

Combinatory integer solution class implementation

macop.solutions.IntegerSolution

Integer solution class implementation

macop.solutions.Solution

Abstract solution class