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wiki:Analyzer

Version 5 (modified by mkofler, 14 years ago) (diff)

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Analyzer

Analyzers are HeuristicLab 3.3 operators that implement the IAnalyzer interface. There are a couple of general purpose Analyzers, such as the QualityAnalyzer or the MultiAnalyzer as well as encoding and problem specific Analyzers.


1. General

1.1 MultiAnalyzer

An analyzer which applies arbitrary many other analyzers. It is used as a parameter in all currently implemented problems (Evolution Strategy?, Genetic Algorithm? etc.) to ensure easy extendability.

For example, if you open the GA for the ch130 problem? sample on the Optimizer Start Page, navigate to the Parameters tab and click on the Analyzer property, you will see the following list of sub-Analyzers:

The BestAverageWorstQualityAnalyzer comes from the genetic algorithm and the BestTSPSolutionAnalyzer was provided by the TSP problem. This wiring also works if you configure your own algorithm in the Optimizer. Opening a new Evolution Strategy algorithm and loading a Griewank test function as problem will result in a BestAverageWorstQualityAnalyzer and a BestSingleObjectiveTestFunctionSolutionAnalyzer. You can of course add additional Analyzers via the GUI.

Operator Parameters:

Parameter Description
UpdateInterval The interval in which the contained analyzers should be applied (Default: 1)
UpdateCounter The value which counts how many times the MultiAnalyzer was called since the last update.

1.2 MinAverageMaxValueAnalyzer

An operator which analyzes the minimum, average and maximum of a value in the scope tree.

1.3 BestAverageWorstQualityAnalyzer

An operator which analyzes the best, average and worst quality of solutions in the scope tree.

1.4 QualityAnalyzer

An operator which analyzes the quality of solutions in the scope tree.

1.5 ValueAnalyzer

An operator which analyzes a value in the scope tree.


2. Tabu Search

2.1 TabuNeighborhoodAnalyzer

Operator Parameters:

Parameter Description
IsTabu A value that determines if a move is tabu or not.
PercentTabu Indicates how much of the neighborhood is tabu.
Results The result collection where the value should be stored.

3. Artificial Ant Problem

3.1 BestAntTrailAnalyzer

An operator for analyzing the best ant trail of an Artificial Ant Problem?.

Operator Parameters:

Parameter Description
BestSolution The visual representation of the best ant trail.
MaxTimeSteps The maximal time steps that the artificial ant has available to collect all food items.
Quality The qualities of the artificial ant solutions which should be visualized.
Results The result collection where the best artificial ant solution should be stored.
SymbolicExpressionTree The artificial ant solutions from which the best solution should be visualized.
World The world with food items for the artificial ant.

4. Knapsack Problem

4.1 BestKnapsackSolutionAnalyzer

An operator for analyzing the best solution for a Knapsack Problem?.

Operator Parameters:

Parameter Description
BestKnownQuality The quality of the best known solution.
BestKnownSolution The best known solution.
BestSolution The best knapsack solution.
BinaryVector The knapsack solutions from which the best solution should be visualized.
KnapsackCapacity Capacity of the Knapsack.
Maximization True if the problem is a maximization problem.
Quality The qualities of the knapsack solutions which should be visualized.
Results The result collection where the knapsack solution should be stored.
Values The values of the items.
Weights The weights of the items.

5. OneMax Problem

5.1 BestOneMaxSolutionAnalyzer

An operator for analyzing the best solution for a OneMax Problem.

Operator Parameters:

Parameter Description
BestKnownQuality The quality of the best known solution.
BestKnownSolution The best known solution.
BinaryVector The Onemax solutions from which the best solution should be visualized.
Maximization True if the problem is a maximization problem.
Quality The qualities of the Onemax solutions which should be visualized.
Results The result collection where the Onemax solution should be stored.

6. Single Objective Test Function Problem

6.1 BestSingleObjectiveTestFunctionSolutionAnalyzer

An operator for analyzing the best solution for a SingleObjectiveTestFunction problem.


7. Travelling Salesman Problem

7.1 BestTSPSolutionAnalyzer

An operator for analyzing the best solution of a Travelling Salesman Problem? given in path representation using city coordinates.

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