Determines the feasibility with respect to nonlinear constraints. Also,max(sqrt(eps),ConstraintTolerance)determines feasibility with respect to linear constraints.

For an options structure, useTolCon．

Positive scalar |{1e-3}

CreationFcn

I*Function that creates the initial population. Specify as a name of a built-in creation function or a function handle. SeePopulation Options．

{'gacreationuniform'}|{'gacreationlinearfeasible'}*|Custom creation function

CrossoverFcn

I*Function that the algorithm uses to create crossover children. Specify as a name of a built-in crossover function or a function handle. SeeCrossover Options．

{'crossoverscattered'}forga,{'crossoverintermediate'}*forgamultiobj|'crossoverheuristic'|'crossoversinglepoint'|'crossovertwopoint'|'crossoverarithmetic'|Custom crossover function

CrossoverFraction

The fraction of the population at the next generation, not including elite children, that the crossover function creates.

Positive scalar |{0.8}

Display

Level of display.

'off'|'iter'|'diagnose'|{'final'}

DistanceMeasureFcn

Function that computes distance measure of individuals. Specify as a name of a built-in distance measure function or a function handle. The value applies to decision variable or design space (genotype) or to function space (phenotype). The default'distancecrowding'is in function space (phenotype). Forgamultiobjonly. SeeMultiobjective Options．

For an options structure, use a function handle, not a name.

{'distancecrowding'}means the same as{@distancecrowding,'phenotype'}|{@distancecrowding,'genotype'}|Custom distance function

EliteCount

NMPositive integer specifying how many individuals in the current generation are guaranteed to survive to the next generation. Not used ingamultiobj．

Positive integer |{ceil(0.05*PopulationSize)}|{0.05*(default PopulationSize)}for mixed-integer problems

FitnessLimit

NMIf the fitness function attains the value ofFitnessLimit, the algorithm halts.

Scalar |{-Inf}

FitnessScalingFcn

Function that scales the values of the fitness function. Specify as a name of a built-in scaling function or a function handle. Option unavailable forgamultiobj．

{'fitscalingrank'}|'fitscalingshiftlinear'|'fitscalingprop'|'fitscalingtop'|Custom fitness scaling function

The algorithm stops if the average relative change in the best fitness function value overMaxStallGenerationsgenerations is less than or equal toFunctionTolerance．IfStallTestis'geometricWeighted', then the algorithm stops if theweightedaverage relative change is less than or equal toFunctionTolerance．

Forgamultiobj, the algorithm stops when the geometric average of the relative change in value of the spread overoptions.MaxStallGenerationsgenerations is less thanoptions.FunctionTolerance, and the final spread is less than the mean spread over the pastoptions.MaxStallGenerationsgenerations. Seegamultiobj Algorithm．

For an options structure, useTolFun．

Positive scalar |{1e-6}forga,{1e-4}forgamultiobj

HybridFcn

I*Function that continues the optimization aftergaterminates. Specify as a name or a function handle.

Alternatively, a cell array specifying the hybrid function and its options. Seega Hybrid Function．

Forgamultiobj, the only hybrid function is@fgoalattain．Seegamultiobj Hybrid Function．

SeeWhen to Use a Hybrid Function．

Function name or handle |'fminsearch' | 'patternsearch' | 'fminunc' | 'fmincon' | {[]}

or

1-by-2 cell array |{@solver, hybridoptions}, wheresolver = fminsearch,patternsearch,fminunc, orfmincon{[]}

InitialPenalty

NMI*Initial value of penalty parameter

Positive scalar |{10}

InitialPopulationMatrix

Initial population used to seed the genetic algorithm. Has up toPopulationSizerows andNcolumns, whereNis the number of variables. You can pass a partial population, meaning one with fewer thanPopulationSizerows. In that case, the genetic algorithm usesCreationFcnto generate the remaining population members. SeePopulation Options

For an options structure, useInitialPopulation．

Matrix |{[]}

InitialPopulationRange

Matrix or vector specifying the range of the individuals in the initial population. Applies togacreationuniformcreation function.gashifts and scales the default initial range to match any finite bounds.

For an options structure, usePopInitRange．

Matrix or vector |{[-10;10]}for unbounded components,{[-1e4+1;1e4+1]}for unbounded components of integer-constrained problems,{[lb;ub]}for bounded components, with the default range modified to match one-sided bounds.

InitialScoresMatrix

I*Initial scores used to determine fitness. Has up toPopulationSizerows and hasNfcolumns, whereNfis the number of fitness functions (1forga, greater than1forgamultiobj). You can pass a partial scores matrix, meaning one with fewer thanPopulationSizerows. In that case, the solver fills in the scores when it evaluates the fitness functions.

For an options structure, useInitialScores．

Column vector for single objective | matrix for multiobjective |{[]}

MaxGenerations

Maximum number of iterations before the algorithm halts.

For an options structure, useGenerations．

Positive integer |{100*numberOfVariables}forga,{200*numberOfVariables}forgamultiobj

MaxStallGenerations

The algorithm stops if the average relative change in the best fitness function value overMaxStallGenerationsgenerations is less than or equal toFunctionTolerance．IfStallTestis'geometricWeighted', then the algorithm stops if the weighted average relative change is less than or equal toFunctionTolerance．

Forgamultiobj, the algorithm stops when the geometric average of the relative change in value of the spread overoptions.MaxStallGenerationsgenerations is less thanoptions.FunctionTolerance, and the final spread is less than the mean spread over the pastoptions.MaxStallGenerationsgenerations. Seegamultiobj Algorithm．

For an options structure, useStallGenLimit．

Positive integer |{50}forga,{100}forgamultiobj

MaxStallTime

NMThe algorithm stops if there is no improvement in the objective function forMaxStallTimeseconds, as measured byticandtoc．

For an options structure, useStallTimeLimit．

Positive scalar| {Inf}

MaxTime

The algorithm stops after running afterMaxTimeseconds, as measured byticandtoc．This limit is enforced after each iteration, sogacan exceed the limit when an iteration takes substantial time.

For an options structure, useTimeLimit．

Positive scalar |{Inf}

MigrationDirection

Direction of migration. See迁移选项

'both'|{'forward'}

MigrationFraction

Scalar from 0 through 1 specifying the fraction of individuals in each subpopulation that migrates to a different subpopulation. See迁移选项

Scalar |{0.2}

MigrationInterval

Positive integer specifying the number of generations that take place between migrations of individuals between subpopulations. See迁移选项．

Positive integer |{20}

MutationFcn

I*Function that produces mutation children. Specify as a name of a built-in mutation function or a function handle. SeeMutation Options．

{'mutationgaussian'}forga,{'mutationadaptfeasible'}*forgamultiobj|'mutationuniform'|Custom mutation function

NonlinearConstraintAlgorithm

Nonlinear constraint algorithm. SeeNonlinear Constraint Solver Algorithms．Option unchangeable forgamultiobj．

For an options structure, useNonlinConAlgorithm．

{'auglag'}forga,{'penalty'}forgamultiobj

OutputFcn

Functions thatgacalls at each iteration. Specify as a function handle or a cell array of function handles. SeeOutput Function Options．

For an options structure, useOutputFcns．

Function handle or cell array of function handles |{[]}

ParetoFraction

Scalar from 0 through 1 specifying the fraction of individuals to keep on the first Pareto front while the solver selects individuals from higher fronts, forgamultiobjonly. SeeMultiobjective Options．

Scalar |{0.35}

PenaltyFactor

NMI*Penalty update parameter.

Positive scalar |{100}

PlotFcn

Function that plots data computed by the algorithm. Specify as a name of a built-in plot function, a function handle, or a cell array of built-in names or function handles. SeePlot Options．

For an options structure, usePlotFcns．

gaorgamultiobj:{[]} | 'gaplotdistance' | 'gaplotgenealogy' | 'gaplotselection' | 'gaplotscorediversity' |'gaplotscores' | 'gaplotstopping' | 'gaplotmaxconstr' |Custom plot function

gaonly:'gaplotbestf' | 'gaplotbestindiv' | 'gaplotexpectation' | 'gaplotrange'

gamultiobjonly:'gaplotpareto' | 'gaplotparetodistance' | 'gaplotrankhist' | 'gaplotspread'

PlotInterval

Positive integer specifying the number of generations between consecutive calls to the plot functions.

Positive integer |{1}

PopulationSize

Size of the population.

Positive integer |{50}whennumberOfVariables <= 5,{200}otherwise |{min(max(10*nvars,40),100)}for mixed-integer problems

PopulationType

Data type of the population. Must be'doubleVector'for mixed integer problems.

'bitstring'|'custom'|{'doubleVector'}

gaignores all constraints whenPopulationTypeis set to'bitString'or'custom'．SeePopulation Options．

SelectionFcn

I*Function that selects parents of crossover and mutation children. Specify as a name of a built-in selection function or a function handle.

gamultiobjuses only'selectiontournament'．

{'selectionstochunif'}forga,{'selectiontournament'}forgamultiobj|'selectionremainder'|'selectionuniform'|'selectionroulette'|Custom selection function

StallTest

NMStopping test type.

'geometricWeighted'|{'averageChange'}

Compute fitness and nonlinear constraint functions in parallel. SeeVectorize and Parallel Options (User Function Evaluation)andHow to Use Parallel Processing in Global Optimization Toolbox．

true|{false}

UseVectorized

Specifies whether functions are vectorized. SeeVectorize and Parallel Options (User Function Evaluation)andVectorize the Fitness Function．

For an options structure, useVectorizedwith the values'on'or'off'．

true|{false}