Multi-Objective optimization using BlackBoxOptim.jl package

Question

I’m running the example code to optimize fitness_schaffer1(x) = (sum(abs2, x), sum(abs2, x .- 2.0)) using Method=:borg_moea.

Code: fitness_schaffer1(x) = (sum(abs2, x), sum(abs2, x .- 2.0))

res = bboptimize(fitness_schaffer1; Method=:borg_moea, FitnessScheme=ParetoFitnessScheme{2}(is_minimizing=true), SearchRange=(-10.0, 10.0), NumDimensions=3, ϵ=0.05, MaxSteps=50000, TraceInterval=1.0, TraceMode=:verbose);

I like to figure out the followings:

1. ParetoFitnessScheme{2} What 2 represents inside the curly brackets?

2. pf = pareto_frontier(res) There are 120-element Vector. Is there any place to change the default value of 120?

3. Details of 120-element Vector Like to figure out what they represent. 120-element Vector{BlackBoxOptim.FrontierIndividualWrapper{Tuple{Float64, Float64}, IndexedTupleFitness{2, Float64}}}: BlackBoxOptim.FrontierIndividualWrapper{Tuple{Float64, Float64}, IndexedTupleFitness{2, Float64}}(BlackBoxOptim.FrontierIndividual{IndexedTupleFitness{2, Float64}}(IndexedTupleFitness{2, Float64}((0.9980588444521499, 6.076993313826746), 7.075052158278895, (19, 121), 1.1024139914614826), [0.5678841558214585, 0.581514678153916, 0.5808675486809768], 3, 23878, 13, 1.64915418452e9), (0.9980588444521499, 6.076993313826746))

''' (0.9980588444521499, 6.076993313826746) = (value of fitness function 1, value of fitness function 2) '''

''' 7.075052158278895 = sum of value of fitness function 1 and value of fitness function 2 '''

''' (19, 121) = any idea what they represent '''

''' 1.1024139914614826 = any idea what this represents '''

''' [0.5678841558214585, 0.581514678153916, 0.5808675486809768] = Candidate values from res or solution vector. '''

''' 3, 23878, 13, 1.64915418452e9 = any idea what they represent '''

''' (0.9980588444521499, 6.076993313826746) = (value of fitness function 1, value of fitness function 2) '''