SIMPLE SOLUTIONS

Manual pages

Scope: PGAPack.

[ Alias ↣ ] Name (section) Brief
PGABuildDatatype(4) Build an MPI datatype for string p in population pop.
PGAChange(8) Repeatedly apply mutation to a string (with an increasing mutation rate) until one or more muta‐.
PGACheckStoppingConditions(8) Returns boolean to indicate if the PGAPack termination conditions --.
PGACheckSum(5) Maps a string to a number to be used a verification check PGA_DATATYPE_USER is not supported.
PGAClearDebugLevel(3) Turn off a debul level.
PGAClearDebugLevelByName(3) Turn off debugging of the named function.
PGACopyIndividual(8) Copies string p1 in population pop1 to position p2 in population pop2.
PGACreate(8) Creates an uninitialized context variable. The Fortran version of this function call contains.
PGACrossover(3) Performs crossover on two parent strings to create two child strings (via side-effect).
PGADebugPrint(3) Write debugging information.
PGADestroy(8) Deallocate memory for this instance of PGAPack, if this context initialized MPI, finalize MPI as.
PGADone(8) Returns PGA_TRUE if the stopping conditions have been met, otherwise returns false.
PGADuplicate(8) Determines if a specified string is a duplicate of one already in an existing population.
PGAEncodeIntegerAsBinary(1) Encodes an integer value as a binary string.
PGAEncodeIntegerAsGrayCode(1) Encodes a real value as a binary reflected Gray code sequence.
PGAEncodeRealAsBinary(1) Encodes a real value as a binary string.
PGAEncodeRealAsGrayCode(1) Encodes a real value as a binary reflected Gray code sequence.
PGAError(6) Reports error messages. Prints out the message supplied, and the value of a piece of data. Termi‐.
PGAEvaluate(1) Calls a user-specified function to return an evaluation of each string in the population.
PGAFitness(1) Maps the user's evaluation function value to a fitness value.
PGAGetBestIndex(5) Returns the index of the string with the best evaluation function value in population pop.
PGAGetBinaryAllele(1) Returns the value of a (binary) allele in a PGA_DATATYPE_BINARY string.
PGAGetBinaryInitProb(2) Returns the probability that an allele will be randomly initialized to "1" in a.
PGAGetCharacterAllele(1) Returns the value of character allele in a PGA_DATATYPE_CHARACTER string.
PGAGetCommunicator(4) Returns the default communicator used when PGARun is called.
PGAGetCrossoverProb(3) Returns the crossover probability.
PGAGetCrossoverType(3) Returns the type of crossover selected.
PGAGetDataType(8) Returns the data type used by the given context.
PGAGetEvaluation(1) Returns the evaluation function value for string p in population pop.
PGAGetEvaluationUpToDateFlag(1) Returns true/false to indicate whether the evaluate function value is up to.
PGAGetFitness(1) Returns the fitness value for a string.
PGAGetFitnessCmaxValue(1) Returns the value of the multiplier used by PGAFitnessMinCmax.
PGAGetFitnessMinType(1) Returns the type of fitness transformation used for minimization problems.
PGAGetFitnessType(1) Returns the type of fitness transformation used.
PGAGetGAIterValue(8) Returns the number of the current genetic algorithm generation.
PGAGetIntegerAllele(1) Returns the value of allele i of member p in population pop.
PGAGetIntegerFromBinary(1) Interpets a binary string as encoding an integer value and returns the integer value.
PGAGetIntegerFromGrayCode(1) Interpets a binary reflected Gray code sequence as encoding an integer value and.
PGAGetIntegerInitType(2) Returns the type of scheme used to randomly initialize strings of data type.
PGAGetMaxFitnessRank(1) Returns the maximum value used in rank-based fitness.
PGAGetMaxGAIterValue(8) Returns the maximum number of iterations to run.
PGAGetMaxIntegerInitValue(2) Returns the maximum of the range of integers used to randomly initialize integer.
PGAGetMaxMachineDoubleValue(6) Returns the largest double of the current machine.
PGAGetMaxMachineIntValue(6) Returns the largest integer of the current machine.
PGAGetMaxRealInitValue(2) Returns the maximum value used to randomly initialize allele i in a real string.
PGAGetMinIntegerInitValue(2) Returns the minimum of the range of integers used to randomly initialize integer.
PGAGetMinMachineDoubleValue(6) Returns the smallest double of the current machine.
PGAGetMinMachineIntValue(6) Returns the smallest integer of the current machine.
PGAGetMinRealInitValue(2) Returns the minimum value used to randomly initialize allele i in a real string.
PGAGetMutationAndCrossoverFlag(8) Returns true if mutation occurs only when crossover does.
PGAGetMutationBoundedFlag(3) Returns PGA_TRUE or PGA_FALSE to indicate whether mutated integer strings remain.
PGAGetMutationIntegerValue(3) Returns the value of the multiplier used to mutate PGA_DATATYPE_INTEGER strings.
PGAGetMutationOrCrossoverFlag(8) Returns true if mutation only occurs when crossover does not.
PGAGetMutationProb(3) Returns the probability of mutation.
PGAGetMutationRealValue(3) Returns the value of the multiplier used to mutate PGA_DATATYPE_REAL strings with.
PGAGetMutationType(3) Returns the type of mutation used.
PGAGetNoDuplicatesFlag(8) Returns PGA_TRUE if duplicates are not allowed, else returns PGA_FALSE.
PGAGetNumProcs(4) Returns the size of communicator comm in processes.
PGAGetNumReplaceValue(8) Returns the maximum number of strings to replace each generation.
PGAGetOptDirFlag(8) Returns a symbolic constant that represents the direction of optimization.
PGAGetPopReplaceType(8) Returns the symbolic constant used to determine which strings to copy from the old pop‐.
PGAGetPopSize(8) Returns the population size.
PGAGetPrintFrequencyValue(7) Returns how often to print statistics reports.
PGAGetPTournamentProb(3) Returns the probability of selecting the best string in a probabilistic binary tourna‐.
PGAGetRandomInitFlag(2) Returns true/false to indicate whether or not alleles are randomly initialized.
PGAGetRandomSeed(5) Returns the integer to seed random numbers with.
PGAGetRank(4) Returns the rank of the processor in communicator comm. If comm is NULL or a sequential version.
PGAGetRealAllele(1) Returns the value of real-valued allele i in string p in population pop.
PGAGetRealFromBinary(1) Interpets a binary string as encoding a real value and returns the real value it repre‐.
PGAGetRealFromGrayCode(1) Interpets a binary reflected Gray code sequence in a binary string as encoding a real.
PGAGetRealInitType(2) Returns the type of scheme used to randomly initialize strings of data type.
PGAGetRestartAlleleChangeProb(3) Returns the probability with which an allele will be mutated during a restart.
PGAGetRestartFlag(3) Returns whether the algorithm should employ the restart operator.
PGAGetRestartFrequencyValue(3) Returns the number of iterations of no change in the best string after which the.
PGAGetSelectType(3) Returns the type of selection selected.
PGAGetSortedPopIndex(8) Returns a population string index from the array created by PGASortPop().
PGAGetStoppingRuleType(8) Returns a symbolic constant that defines the termination criteria.
PGAGetStringLength(8) Returns the string length.
PGAGetUniformCrossoverProb(3) Returns the probability of a bit being selected from the first child string in.
PGAGetWorstIndex(5) Returns the index of the string with the worst evaluation function value in population pop.
PGAHammingDistance(5) Calculates the mean Hamming distance for a population of binary strings.
PGAMean(5) Calculates the mean value of an array of elements.
PGAMutate(3) This routine performs mutation on a string.
PGAPrintContextVariable(7) Prints the value of all the fields in the context variable.
PGAPrintIndividual(7) Prints the allele values of a string and associated fields (evaluation, fitness, etc.) of.
PGAPrintPopulation(7) Calls PGAPrintIndividual to print each member of a population.
PGAPrintReport(7) Prints genetic algorithm statistics.
PGAPrintString(7) Write the allele values in a string to a file.
PGARandom01(5) Generates a uniform random number on the interval [0,1).
PGARandomFlip(5) Flip a biased coin and return PGA_TRUE if the coin is a "winner.".
PGARandomGaussian(5) Returns an approximation to a Gaussian random number.
PGARandomInterval(5) Returns a uniform random number on the specified interval.
PGARandomUniform(5) Returns a uniform random number on the interval [start,end].
PGARank(1) Returns the rank of a string in a population.
PGAReceiveIndividual(4) Receive an individual from another process.
PGARestart(3) Reseeds a population from the best string.
PGARound(5) Mathematically round a double to an integer, using 0.5 as the cutoff value.
PGARun(8) Highest level routine to execute the genetic algorithm. It is called after PGACreate and PGASetup.
PGARunGM(8) High-level routine to execute the genetic algorithm using the global model.
PGARunMutationAndCrossover(8) Performs crossover and mutation from one population to create the next.
PGARunMutationOrCrossover(8) Performs crossover or mutation (but not both) from one populationto create the.
PGASelect(3) Performs genetic algorithm selection using either the default selection scheme or that specified.
PGASelectNextIndex(3) Returns the index of next individual in internal array that contains the indices deter‐.
PGASendIndividual(4) Transmit an individual to another process.
PGASendReceiveIndividual(4) Send an individual to a process, while receiving a different individual from a dif‐.
PGASetBinaryAllele(1) Sets a binary allele to the specified value.
PGASetBinaryInitProb(2) Specify the probability of initializing an allele to "1" when creating a.
PGASetCharacterAllele(1) Sets the value of an allele in a PGA_DATATYPE_CHARACTER string.
PGASetCharacterInitType(2) Sets a flag to specify whether the character strings will be exclusively lowercase,.
PGASetCommunicator(4) Set the default communicator to use when PGARun is called.
PGASetCrossoverProb(3) Probability that a selected string will undergo crossover.
PGASetCrossoverType(3) Specify the type of crossover to use.
PGASetDebugLevel(3) Turn on a debug level.
PGASetDebugLevelByName(3) Turn on debugging of the named function.
PGASetEvaluation(1) Set the evaluation function value for a string to a specified value.
PGASetEvaluationUpToDateFlag(1) Sets the flag associated with a string to PGA_TRUE or PGA_FLASE to indicate.
PGASetFitnessCmaxValue(1) The value of the multiplier used by PGAFitnessMinCmax so that the worst string has a.
PGASetFitnessMinType(1) Sets the type of algorithm used if a minimization problem is specified to determine how.
PGASetFitnessType(1) Set the type of fitness algorithm to use.
PGASetIntegerAllele(1) Sets the value of a (integer) allele.
PGASetIntegerInitPermute(2) Sets a flag to tell the initialization routines to set each integer-valued gene to.
PGASetIntegerInitRange(2) Sets a flag to tell the initialization routines to set each integer-valued gene to a.
PGASetMaxFitnessRank(1) The value of the parameter Max when using linear ranking for fitness determination.
PGASetMaxGAIterValue(8) Specify the maximum number of iterations for the stopping rule PGA_STOP_MAXITER (which,.
PGASetMaxNoChangeValue(8) Specifiy maximum number of iterations of no change in the evaluation function value.
PGASetMaxSimilarityValue(8) Specifiy the maximum percent of homogeneity of the population before stopping.
PGASetMutationAndCrossoverFlag(8) A boolean flag to indicate if recombination uses both crossover and mutation.
PGASetMutationBoundedFlag(3) If this flag is set to PGA_TRUE, then for Integer and Real strings whenever a gene.
PGASetMutationIntegerValue(3) Set multiplier to mutate PGA_DATATYPE_INTEGER strings with.
PGASetMutationOrCrossoverFlag(8) A boolean flag to indicate if recombination uses exactly one of crossover or.
PGASetMutationProb(3) Specifies the probability that a given allele will be mutated.
PGASetMutationRealValue(3) Set multiplier to mutate PGA_DATATYPE_REAL strings with.
PGASetNoDuplicatesFlag(8) A boolean flag to indicate if duplicate strings are allowed in the population.
PGASetNumReplaceValue(8) Specifies the number of new strings to create each generation.
PGASetPopReplaceType(8) Choose method of sorting strings to copy from old population to new population.
PGASetPopSize(8) Specifies the size of the genetic algorithm population.
PGASetPrintFrequencyValue(7) Specifies the frequency with which genetic algorithm statistics are reported.
PGASetPrintOptions(7) Set flags to indicate what GA statistics should be printed whenever output is printed.
PGASetPTournamentProb(3) Specifies the probability that the string that wins a binary tournament will be.
PGASetRandomInitFlag(2) A boolean flag to indicate whether to randomly initialize alleles.
PGASetRandomSeed(5) Set a seed for the random number generator.
PGASetRealAllele(1) Sets the value of real-valued allele i in string p in population pop.
PGASetRealInitPercent(2) Sets the upper and lower bounds for randomly initializing real-valued genes.
PGASetRealInitRange(2) Sets the upper and lower bounds for randomly initializing real-valued genes.
PGASetRestartAlleleChangeProb(3) Specifies the probability with which an allele will be mutated during a.
PGASetRestartFlag(3) Specifies whether the algorithm should employ the restart operator.
PGASetRestartFrequencyValue(3) Specifies the number of iterations of no change in the best string after which.
PGASetSelectType(3) Specify the type of selection to use.
PGASetStoppingRuleType(8) Specify a stopping criterion.
PGASetUniformCrossoverProb(3) Probability used in uniform crossover to specify that an allele value value be.
PGASetUp(8) Set all uninitialized variables to default values and initialize some internal arrays.
PGASetUserFunction(8) Specifies the name of a user-written function call to provide a specific GA capability.
PGASortPop(8) Creates an (internal) array of indices according to one of three criteria.
PGAStddev(5) Calculates the standard deviation of an array of elements.
PGAUpdateGeneration(8) Updates internal data structures for the next genetic algorithm iteration, and checks if.