MOA-HiGHS Unsupported Objective Function

Specific Domains Optimization (Mathematical)
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5

Hi @jhannyj, welcome to the forum :smile:

MOA is for solving multi-objective (vector-valued) optimization problems, not for finding multiple solutions to a scalar-valued optimization problem.

HiGHS does not support finding multiple solutions.

You could do something like this, where you solve once, add a constraint on optimal objective value, and then try to find a diversity of solutions:

using JuMP, HiGHS
import MultiObjectiveAlgorithms as MOA
model = Model(HiGHS.Optimizer)
@variable(model, x[1:n] >= 0)
@constraint(model, A' * x .>= f)
@objective(model, Min, b' * x)
optimize!(model)
@constraint(model, b' * x == objective_value(model))
@objective(model, Min, x)  # objective is now a vector
set_optimizer(model, () -> MOA.Optimizer(HiGHS.Optimizer))
optimize!(model)
[value(x; result = i) for i in 1:result_count(model)]