Interface UI target

[joaquimg]

import MathOptInterface
const MOI = MathOptInterface
const MOIU = MOI.Utilities

#=
    1 Pure Annealer - working
=#

model = MOI.instantiate(ToQUBO.QuantumAnnealer.Optimizer, with_bridge_type = Float64)

x = MOI.add_variables(model, 2);

for xᵢ in x
    MOI.add_constraint(model, xᵢ, MOI.ZeroOne())
end

# alternatively
#=
x, c = MOI.add_constrained_variables(model, fill(MOI.ZeroOne(), 2))
=#

MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)

MOI.set(
    model,
    MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(),
    MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.([1.0, 1.2], x), 0.0),
);

optimize!(model)

#=
    2 Pure Annealer - faile
=#

model = MOI.instantiate(ToQUBO.QuantumAnnealer.Optimizer, with_bridge_type = Float64)

x = MOI.add_variables(model, 2);

# will fail in `optimize!` because there is no auto conversion from Int to Bin
for xᵢ in x
    MOI.add_constraint(model, xᵢ, MOI.Integer())
end

# alternatively
#=
x, c = MOI.add_constrained_variables(model, fill(MOI.Integer(), 2))
=#

MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)

MOI.set(
    model,
    MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(),
    MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.([1.0, 1.2], x), 0.0),
);

optimize!(model)


#=
    3 QUBO converter
=#

model = MOI.instantiate(
    ()->ToQUBO.Optimizer(annealer = ToQUBO.QuantumAnnealer.Optimizer),
    with_bridge_type = Float64)

x = MOI.add_variables(model, 2);

# will work because ToQUBO.Optimizer will know how to expand an integer variables
# into binaries
for xᵢ in x
    MOI.add_constraint(model, xᵢ, MOI.Integer())
end

MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)

MOI.set(
    model,
    MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(),
    MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.([1.0, 1.2], x), 0.0),
);

optimize!(model)

[pedromxavier]

That looks great! Thanks!

PS: Last example will fail since the variables xᵢ are unbounded. Do you think there is anything we could do about it, appart from yelling at the user about it? I got very interested on the InfiniteOpt.jl package due to quadratures and other stuff I just had in mind before.

[joaquimg]

My bad writing the reference code, we need the bounds. The converter will return an error saying that as early as possible.

Lets talk about InfinitOpt offline.

[bernalde]

I'd be interested in being part of this conversation. You might not know, but the InfintOpt package developer is doing a postdoc at the department I'm currently at (and we're friends). The package is cool too!