Fix typos

docs/src/dev.md

@@ -119,7 +119,7 @@ Evolutionary.tolerance
 
 **Note:** If the class contains the field `Δ`, which holds the current difference
 between last consecutive convergence function evaluations, then the provided
-`Evolutinary.diff` function will work correctly.
+`Evolutionary.diff` function will work correctly.
 Similarly, if the class has the field `tol`, which holds a tolerance value,
 the `Evolutionary.tolerance` method will work correctly.
 

docs/src/selection.md

@@ -3,7 +3,7 @@
 **Selection** is a genetic operator used in EAs for selecting potentially useful solutions from a population for later breeding.
 The EAs are stochastic search methods using the concepts of Mendelian genetics and Darwinian evolution.
 According to Darwin's evolution theory the best ones should survive and create new offspring.
-There are many methods how to select the best individuals, for example roulette wheel selection, Boltzman selection,
+There are many methods how to select the best individuals, for example roulette wheel selection, Boltzmann selection,
 tournament selection, rank selection, steady state selection and some others.
 
 ## Selection Interface

examples/SymbolicRegression.ipynb

@@ -421,7 +421,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We need to the symbol collection `rand` function which will alow to generate numerical constanst in addition to the symbolical variables. For each symbol we specify its arity."
+    "We need to the symbol collection `rand` function which will alow to generate numerical constants in addition to the symbolical variables. For each symbol we specify its arity."
    ]
   },
   {

src/ga.jl

@@ -11,7 +11,7 @@ Floating number specifies fraction of population.
 - `selection`: [Selection](@ref) function (default: [`tournament`](@ref))
 - `crossover`: [Crossover](@ref) function (default: [`genop`](@ref))
 - `mutation`: [Mutation](@ref) function (default: [`genop`](@ref))
-- `after_op`: a function that is executed on each individual afrer mutation operations (default: `identity`)
+- `after_op`: a function that is executed on each individual after mutation operations (default: `identity`)
 - `metrics` is a collection of convergence metrics.
 """
 struct GA{T1,T2,T3,T4} <: AbstractOptimizer
@@ -77,7 +77,7 @@ function update_state!(objfun, constraints, state, parents::AbstractVector{IT},
     populationSize = method.populationSize
     rng = options.rng
 
-    # create an offspring popultation
+    # create an offspring population
     offspring = similar(parents)
 
     # select offspring