From 4f26361eb08aa09334d1eea0a124110c20d809ce Mon Sep 17 00:00:00 2001 From: Eduardo Pedroni Date: Sat, 18 Oct 2014 15:21:45 +0200 Subject: Moved javadocs to a different repository for hosting, updated README --- .../modules/problem/TravellingSalesmanProblem.html | 433 --------------------- 1 file changed, 433 deletions(-) delete mode 100644 doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html (limited to 'doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html') diff --git a/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html b/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html deleted file mode 100644 index 4a2d0c9..0000000 --- a/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html +++ /dev/null @@ -1,433 +0,0 @@ - - - - - -TravellingSalesmanProblem - - - - - - - - -
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jcgp.backend.modules.problem
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Class TravellingSalesmanProblem

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    public class TravellingSalesmanProblem
-extends Problem
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    Travelling salesman problem -

    - Using this problem type, travelling salesman tours can be evolved. - parseData() must be used to load the desired city - coordinates in the standard .tsp format.
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    Author:
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    Eduardo Pedroni
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    See Also:
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    TravellingSalesmanFunctions
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      Constructor Detail

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        TravellingSalesmanProblem

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        public TravellingSalesmanProblem(Resources resources)
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        Construct a new instance of TravellingSalesmanProblem.
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        Parameters:
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        resources - a reference to the experiment's resources.
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      Method Detail

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        evaluate

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        public void evaluate(Population population,
-                     Resources resources)
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        Description copied from class: Problem
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        The most important method of the problem type. This is called once - per generation, when the new population has been generated. -

        - The basic functionality of this method is to loop through all chromosomes - in the population and decode them according to the problem type. The - fitness of each chromosome is then calculated using the problem data - or otherwise (subjective problem types such as art generation might - leave fitness evaluations up to the user) and assigned to the appropriate - chromosome. -

        - In addition, realisations of this method should update the value of - bestFitness as appropriate, since the value of this parameter is displayed - if a GUI is in use.
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        Specified by:
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        evaluate in class Problem
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        Parameters:
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        population - the population to be evaluated.
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        resources - parameters and utilities for optional reference.
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        isPerfectSolution

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        public boolean isPerfectSolution(Chromosome fittest)
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        Description copied from class: Problem
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        Used to assert whether a given chromosome is a perfect solution - to the problem. It is up to the problem to define what qualifies - a perfect solution, as some problems (subject ones such as music and - art evolution, for example) might not have perfect solutions at all. -

        - Note that if this method returns true, the experiment will move on - to the next run, or finish if no more runs are left.
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        Specified by:
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        isPerfectSolution in class Problem
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        Parameters:
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        fittest - the potentially perfect chromosome.
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        Returns:
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        true if the argument is a perfect solution.
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        parseProblemData

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        public void parseProblemData(java.io.File file,
-                             ModifiableResources resources)
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        Description copied from class: Problem
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        Parses the specified file and uses the parsed data to - set up the problem type instance appropriately. Any necessary - resource changes can be performed using the provided ModifiableResources - instance. -

        - In addition, realisations of this method should update the value of - maxFitness where appropriate, as this may be displayed to the user - if a GUI is in use.
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        Specified by:
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        parseProblemData in class Problem
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        Parameters:
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        file - the data file to parse.
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        resources - a modifiable reference to the experiment's resources.
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        isImprovement

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        public boolean isImprovement(Chromosome fittest)
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        Description copied from class: Problem
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        Used to assert whether a given chromosome is an improvement over - the current best chromosome. A typical implementation of this method - will simply compare chromosome fitness values, though the problem type - is free to implement this in any way.
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        Specified by:
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        isImprovement in class Problem
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        Parameters:
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        fittest - the potentially fitter chromosome.
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        Returns:
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        true if the argument is fitter than the currently fittest chromosome.
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Skip navigation links
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