ERROR: No set_candidates! method defined for BlackBoxOptim.GeneratingSetSearcher

[hiiroo]

Hello everyone and thanks for the great library! I have a problem with starting an optimization for probabilistic_descent with initial candidates: code sample and the stack trace given below. I am using Julia 1.9 rc right now. I can give you more details if you need them. vInitial is a vector of length 24.

res = bboptimize(fitnessfunc, [vInitial];
	Method=:probabilistic_descent,
	SearchRange = (-2, 2),
	NumDimensions = 24,
	MaxSteps=100,
	TargetFitness=(0.0)
)

and, the stack trace;

ERROR: No set_candidates! method defined for BlackBoxOptim.GeneratingSetSearcher{BlackBoxOptim.ProblemEvaluator{Float64, Float64, TopListArchive{Float64, ScalarFitnessScheme{true}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, BlackBoxOptim.MirroredRandomDirectionGen, RandomBound{ContinuousRectSearchSpace}}
Stacktrace:
  [1] error(s::String)
    @ Base ./error.jl:35
  [2] set_candidates!(o::BlackBoxOptim.GeneratingSetSearcher{BlackBoxOptim.ProblemEvaluator{Float64, Float64, TopListArchive{Float64, ScalarFitnessScheme{true}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, BlackBoxOptim.MirroredRandomDirectionGen, RandomBound{ContinuousRectSearchSpace}}, x0::Vector{Vector{Float64}})
    @ BlackBoxOptim ~/.julia/packages/BlackBoxOptim/I3lfp/src/optimizer.jl:102
  [3] bboptimize(optctrl::BlackBoxOptim.OptController{BlackBoxOptim.GeneratingSetSearcher{BlackBoxOptim.ProblemEvaluator{Float64, Float64, TopListArchive{Float64, ScalarFitnessScheme{true}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, BlackBoxOptim.MirroredRandomDirectionGen, RandomBound{ContinuousRectSearchSpace}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, x0::Vector{Vector{Float64}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ BlackBoxOptim ~/.julia/packages/BlackBoxOptim/I3lfp/src/bboptimize.jl:75
  [4] bboptimize(optctrl::BlackBoxOptim.OptController{BlackBoxOptim.GeneratingSetSearcher{BlackBoxOptim.ProblemEvaluator{Float64, Float64, TopListArchive{Float64, ScalarFitnessScheme{true}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, BlackBoxOptim.MirroredRandomDirectionGen, RandomBound{ContinuousRectSearchSpace}}, FunctionBasedProblem{var"#157#159"{Vector{∅}}, ScalarFitnessScheme{true}, ContinuousRectSearchSpace, Float64}}, x0::Vector{Vector{Float64}})
    @ BlackBoxOptim ~/.julia/packages/BlackBoxOptim/I3lfp/src/bboptimize.jl:64
  [5] bboptimize(functionOrProblem::Function, x0::Vector{Vector{Float64}}, parameters::Dict{Symbol, ∅}; kwargs::Base.Pairs{Symbol, ∅, NTuple{6, Symbol}, NamedTuple{(:Method, :SearchRange, :ϵ, :NumDimensions, :MaxSteps, :TargetFitness), Tuple{Symbol, Tuple{Int64, Int64}, Float64, Int64, Int64, Float64}}})
    @ BlackBoxOptim ~/.julia/packages/BlackBoxOptim/I3lfp/src/bboptimize.jl:88
  [6] bboptimize
    @ ~/.julia/packages/BlackBoxOptim/I3lfp/src/bboptimize.jl:86 [inlined]

[hoasxyz]

@hiiroo In the Borg MOEA, it runs successfully with a single initial solution. But when setting multiple initial solutions, I encounter a problem similar to yours:

Success

res_his_borg = bboptimize(maximin_operator, initial_pop_sim[1]; Method = :borg_moea, FitnessScheme = ParetoFitnessScheme{3}(is_minimizing = false), 
                    SearchRange = vcat(repeat([(400.0, 24000.0)], 20), repeat([(0.01, 1.0)], 25), repeat([(-1.0, 1.0)], 25), repeat([(0.0, 1.0)], 2)),  NumDimensions = 72,
                    MaxTime = 60, # MaxFuncEvals = 20000, MaxSteps = 50000, PopulationSize = 100, 
                    ϵ = [4, 30, 0.5], TraceInterval = 1.0, TraceMode = :compact);

Fail

res_his_borg = bboptimize(maximin_operator, initial_pop_sim; Method = :borg_moea, FitnessScheme = ParetoFitnessScheme{3}(is_minimizing = false), 
                    SearchRange = vcat(repeat([(400.0, 24000.0)], 20), repeat([(0.01, 1.0)], 25), repeat([(-1.0, 1.0)], 25), repeat([(0.0, 1.0)], 2)),  NumDimensions = 72,
                    MaxTime = 60, # MaxFuncEvals = 20000, MaxSteps = 50000, PopulationSize = 100, 
                    ϵ = [4, 30, 0.5], TraceInterval = 1.0, TraceMode = :compact);

with

ERROR: No set_candidates! method defined for BlackBoxOptim.BorgMOEA{EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}, BlackBoxOptim.ProblemEvaluator{Tuple{Float64, Float64, Float64}, IndexedTupleFitness{3, Float64}, EpsBoxArchive{3, Float64, EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, FitPopulation{IndexedTupleFitness{3, Float64}}, FixedGeneticOperatorsMixture, RandomBound{ContinuousRectSearchSpace}}
Stacktrace:
 [1] error(s::String)
   @ Base .\error.jl:35
 [2] set_candidates!(o::BlackBoxOptim.BorgMOEA{EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}, BlackBoxOptim.ProblemEvaluator{Tuple{Float64, Float64, Float64}, IndexedTupleFitness{3, Float64}, EpsBoxArchive{3, Float64, EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, FitPopulation{IndexedTupleFitness{3, Float64}}, FixedGeneticOperatorsMixture, RandomBound{ContinuousRectSearchSpace}}, x0::Vector{Vector{Float64}})
   @ BlackBoxOptim E:\.julia\packages\BlackBoxOptim\I3lfp\src\optimizer.jl:102
 [3] bboptimize(optctrl::BlackBoxOptim.OptController{BlackBoxOptim.BorgMOEA{EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}, BlackBoxOptim.ProblemEvaluator{Tuple{Float64, Float64, Float64}, IndexedTupleFitness{3, Float64}, EpsBoxArchive{3, Float64, EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, FitPopulation{IndexedTupleFitness{3, Float64}}, FixedGeneticOperatorsMixture, RandomBound{ContinuousRectSearchSpace}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, x0::Vector{Vector{Float64}}; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
   @ BlackBoxOptim E:\.julia\packages\BlackBoxOptim\I3lfp\src\bboptimize.jl:75
 [4] bboptimize(optctrl::BlackBoxOptim.OptController{BlackBoxOptim.BorgMOEA{EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}, BlackBoxOptim.ProblemEvaluator{Tuple{Float64, Float64, Float64}, IndexedTupleFitness{3, Float64}, EpsBoxArchive{3, Float64, EpsBoxDominanceFitnessScheme{3, Float64, false, typeof(sum)}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, FitPopulation{IndexedTupleFitness{3, Float64}}, FixedGeneticOperatorsMixture, RandomBound{ContinuousRectSearchSpace}}, FunctionBasedProblem{typeof(maximin_operator), ParetoFitnessScheme{3, Float64, false, typeof(sum)}, ContinuousRectSearchSpace, Nothing}}, x0::Vector{Vector{Float64}})
   @ BlackBoxOptim E:\.julia\packages\BlackBoxOptim\I3lfp\src\bboptimize.jl:64
 [5] bboptimize(functionOrProblem::Function, x0::Vector{Vector{Float64}}, parameters::Dict{Symbol, Any}; kwargs::Base.Pairs{Symbol, Any, NTuple{8, Symbol}, NamedTuple{(:Method, :FitnessScheme, :SearchRange, :NumDimensions, :MaxTime, :ϵ, :TraceInterval, :TraceMode), Tuple{Symbol, ParetoFitnessScheme{3, Float64, false, typeof(sum)}, Vector{Tuple{Float64, Float64}}, Int64, Int64, Vector{Float64}, Float64, Symbol}}})
   @ BlackBoxOptim E:\.julia\packages\BlackBoxOptim\I3lfp\src\bboptimize.jl:88
 [6] top-level scope
   @ e:\1WHU\item\jsj\Operation_jxsk_newvfh_newsim_parallel_borg.jl:559