AlgorithmEvolutionary 0.82.1 Latest
Kwalitee Issues
 use_strict

Add 'use strict' (or its equivalents) to all modules, or convince us that your favorite module is wellknown enough and people can easily see the modules are strictly written.
Error: Algorithm::Evolutionary
 meta_yml_declares_perl_version

If you are using Build.PL define the {requires}{perl} = VERSION field. If you are using MakeMaker (Makefile.PL) you should upgrade ExtUtils::MakeMaker to 6.48 and use MIN_PERL_VERSION parameter. Perl::MinimumVersion can help you determine which version of Perl your module needs.
 use_warnings

Add 'use warnings' (or its equivalents) to all modules, or convince us that your favorite module is wellknown enough and people can easily see the modules warn when something bad happens.
Error: Algorithm::Evolutionary
 consistent_version

Split the distribution, or fix the version numbers to make them consistent (use the highest version number to avoid version downgrade).
Error: 0.082001,1.005,1.102,1.2,1.3,1.4,1.5,1.7,3.0,3.000,3.001,3.002,3.007,3.1,3.104,3.106,3.2,3.3,3.4,3.5,3.6,3.7
 meta_yml_has_provides

Add all modules contained in this distribution to the META.yml field 'provides'. Module::Build or Dist::Zilla::Plugin::MetaProvides do this automatically for you.
Modules
Name  Abstract  Version  View 

Algorithm::Evolutionary  Perl module for performing paradigmfree evolutionary algorithms.  0.082001  metacpan 
Algorithm::Evolutionary::Experiment  Class for setting up an experiment with algorithms and population  3.4  metacpan 
Algorithm::Evolutionary::Fitness::Any  Façade for any function so that it can be used as fitness  3.2  metacpan 
Algorithm::Evolutionary::Fitness::Base  Base class for fitness functions  3.1  metacpan 
Algorithm::Evolutionary::Fitness::ECC  Error Correcting codes problem generator  3.2  metacpan 
Algorithm::Evolutionary::Fitness::Knapsack  Fitness function for the knapsack problem  3.1  metacpan 
Algorithm::Evolutionary::Fitness::MMDP  Massively Multimodal Deceptive Problem  3.0  metacpan 
Algorithm::Evolutionary::Fitness::ONEMAX  Fitness function for the ONEMAX or countones problem  3.0  metacpan 
Algorithm::Evolutionary::Fitness::P_Peaks  P Peaks problem generator  3.4  metacpan 
Algorithm::Evolutionary::Fitness::Rastrigin  Implementation of Rastrigin's function  3.3  metacpan 
Algorithm::Evolutionary::Fitness::Royal_Road  Mitchell's Royal Road function  3.1  metacpan 
Algorithm::Evolutionary::Fitness::String  Base class for stringbased fitness functors  3.0  metacpan 
Algorithm::Evolutionary::Fitness::Trap  'Trap' fitness function for evolutionary algorithms  3.2  metacpan 
Algorithm::Evolutionary::Fitness::ZDT1  ZitzlerDebThiele #1 Multiobjective test function  3.001  metacpan 
Algorithm::Evolutionary::Fitness::wP_Peaks  wP Peaks problem generator  weighted version of P_Peaks  3.002  metacpan 
Algorithm::Evolutionary::Hash_Wheel  Random selector of things depending on probabilities  1.2  metacpan 
Algorithm::Evolutionary::Individual::Any  Wrapper around any Perl data structure, turns it into a I<Chromosome>  3.0  metacpan 
Algorithm::Evolutionary::Individual::Base  Base class for chromosomes that knows how to build them, and has some helper methods.  3.3  metacpan 
Algorithm::Evolutionary::Individual::BitString  Classic bitstring individual for evolutionary computation; usually called I<chromosome>  3.4  metacpan 
Algorithm::Evolutionary::Individual::Bit_Vector  Classic bitstring individual for evolutionary computation; usually called chromosome, and using a different implementation from Algorithm::Evolutionary::Individual::BitString  3.1  metacpan 
Algorithm::Evolutionary::Individual::String  A character string to be evolved. Useful mainly in word games  3.7  metacpan 
Algorithm::Evolutionary::Individual::Tree  3.1  metacpan  
Algorithm::Evolutionary::Individual::Vector  Array as an individual for evolutionary computation  3.2  metacpan 
Algorithm::Evolutionary::Op::Animated_GIF_Output  Creates an animated GIF, a frame per generation. Useful for binary strings.  1.005  metacpan 
Algorithm::Evolutionary::Op::ArithCrossover  Arithmetic crossover operator; performs the average of the n parents crossed  3.001  metacpan 
Algorithm::Evolutionary::Op::Base  Base class for Algorithm::Evolutionary operators,  3.3  metacpan 
Algorithm::Evolutionary::Op::Bitflip  Bitflip mutation  3.4  metacpan 
Algorithm::Evolutionary::Op::Breeder  Even more customizable single generation for an evolutionary algorithm.  1.4  metacpan 
Algorithm::Evolutionary::Op::Breeder_Diverser  Like Breeder, only it tries to cross only individuals that are different  1.7  metacpan 
Algorithm::Evolutionary::Op::CX  3.2  metacpan  
Algorithm::Evolutionary::Op::CanonicalGA  Canonical Genetic Algorithm, with any representation  3.6  metacpan 
Algorithm::Evolutionary::Op::Canonical_GA_NN  Canonical Genetic Algorithm that does not rank population  3.6  metacpan 
Algorithm::Evolutionary::Op::ChangeLengthMutation  Increases/decreases by one atom the length of the string  3.1  metacpan 
Algorithm::Evolutionary::Op::Combined  Combinator of several operators of the same arity, unary or binary  1.2  metacpan 
Algorithm::Evolutionary::Op::Convergence_Terminator  Checks for termination of an algorithm, returns true if a certain percentage of the population is the same  3.1  metacpan 
Algorithm::Evolutionary::Op::Creator  Operator that generates groups of individuals, of the intended class  3.1  metacpan 
Algorithm::Evolutionary::Op::Crossover  npoint crossover operator; puts fragments of the second operand into the first operand  3.002  metacpan 
Algorithm::Evolutionary::Op::DeltaTerm  Termination condition for an algorithm; checks that the difference of the best to a target is less than a delta  3.0  metacpan 
Algorithm::Evolutionary::Op::EDA_step  Single step for a Estimation of Distribution Algorithm  1.5  metacpan 
Algorithm::Evolutionary::Op::Easy  evolutionary algorithm, single generation, with variable operators.  3.5  metacpan 
Algorithm::Evolutionary::Op::Easy_MO  Multiobjecttive evolutionary algorithm, single generation, with variable operators  3.6  metacpan 
Algorithm::Evolutionary::Op::Eval::General  General and simple population evaluator  3.000  metacpan 
Algorithm::Evolutionary::Op::Eval::MO_Rank  Multiobjective evaluator based on Pareto rank  3.002  metacpan 
Algorithm::Evolutionary::Op::FullAlgorithm  Skeleton class for a fullyfeatured evolutionary algorithm  3.0  metacpan 
Algorithm::Evolutionary::Op::GaussianMutation  Changes numeric chromosome components following the gaussian distribution.  3.4  metacpan 
Algorithm::Evolutionary::Op::Gene_Boundary_Crossover  npoint crossover operator that restricts crossing point to gene boundaries  3.002  metacpan 
Algorithm::Evolutionary::Op::GeneralGeneration  Customizable single generation for an evolutionary algorithm.  3.2  metacpan 
Algorithm::Evolutionary::Op::Generation_Skeleton  Even more customizable single generation for an evolutionary algorithm.  3.3  metacpan 
Algorithm::Evolutionary::Op::GenerationalTerm  Checks for termination of an algorithm.  3.0  metacpan 
Algorithm::Evolutionary::Op::IncMutation  Increments/decrements by one the value of one of the components of the string, takes into account the char class  3.001  metacpan 
Algorithm::Evolutionary::Op::Inverover  Michalewicz's inverover Operator.  3.0  metacpan 
Algorithm::Evolutionary::Op::LinearFreezer  Used by Simulated Annealing algorithms, reduces temperature lineally.  3.1  metacpan 
Algorithm::Evolutionary::Op::Mutation  Bitflip mutation, changes several bits in a bitstring, depending on the probability  3.2  metacpan 
Algorithm::Evolutionary::Op::NoChangeTerm  Checks for termination of an algorithm; terminates when several generations transcur without change  3.0  metacpan 
Algorithm::Evolutionary::Op::Novelty_Mutation  Mutation guaranteeing new individual is not in the population  3.001  metacpan 
Algorithm::Evolutionary::Op::Permutation  Permutation. Got it?  3.7  metacpan 
Algorithm::Evolutionary::Op::Population_Output  Flexible population printing class  3.001  metacpan 
Algorithm::Evolutionary::Op::QuadXOver  Npoint crossover operator that changes operands  3.104  metacpan 
Algorithm::Evolutionary::Op::Quad_Crossover_Diff  Uniform crossover, but interchanges only those atoms that are different  1.102  metacpan 
Algorithm::Evolutionary::Op::Replace_Different  Incorporate individuals into the population replacing the worst ones but only if they are different.  1.3  metacpan 
Algorithm::Evolutionary::Op::Replace_Worst  Incorporate individuals into the population replacing the worst ones  3.2  metacpan 
Algorithm::Evolutionary::Op::RouletteWheel  Fitnessproportional selection, using a roulette wheel.  3.1  metacpan 
Algorithm::Evolutionary::Op::Selector  Abstract base class for population selectors  3.0  metacpan 
Algorithm::Evolutionary::Op::SimulatedAnnealing  3.1  metacpan  
Algorithm::Evolutionary::Op::Storing  Applies the op and keeps the result  3.001  metacpan 
Algorithm::Evolutionary::Op::StringRand  randomly change chars in a string  3.001  metacpan 
Algorithm::Evolutionary::Op::String_Mutation  Single character string mutation  3.007  metacpan 
Algorithm::Evolutionary::Op::Tournament_Selection  Tournament selector, takes individuals from one population and puts them into another  1.5  metacpan 
Algorithm::Evolutionary::Op::TreeMutation  GPlike mutation operator for trees  3.1  metacpan 
Algorithm::Evolutionary::Op::Uniform_Crossover  interchanges a set of atoms from one parent to the other.  3.2  metacpan 
Algorithm::Evolutionary::Op::Uniform_Crossover_Diff  Uniform crossover, but interchanges only those atoms that are different  3.106  metacpan 
Algorithm::Evolutionary::Op::VectorCrossover  Crossover for L<Algorithm::Evolutionary::Individual::Vector>.  3.1  metacpan 
Algorithm::Evolutionary::Run  Class for setting up an experiment with algorithms and population  3.2  metacpan 
Algorithm::Evolutionary::Utils  Container module with a hodgepodge of functions  3.4  metacpan 
Algorithm::Evolutionary::Wheel  Random selector of things depending on probabilities  3.6  metacpan 