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Solving Max x * y returns "Optimal" instead of declaring the QP to be non-convex. See the JuMP example:
Max x * y
julia> using JuMP, HiGHS julia> model = Model(HiGHS.Optimizer) A JuMP Model Feasibility problem with: Variables: 0 Model mode: AUTOMATIC CachingOptimizer state: EMPTY_OPTIMIZER Solver name: HiGHS julia> @variable(model, x) x julia> @variable(model, y) y julia> @objective(model, Max, x * y) x*y julia> optimize!(model) Running HiGHS 1.7.0 (git hash: 50670fd4c): Copyright (c) 2024 HiGHS under MIT licence terms Coefficient ranges: Cost [0e+00, 0e+00] Bound [0e+00, 0e+00] Iteration, Runtime, ObjVal, NullspaceDim 0, 0.000214, 0.000000, 2 2, 0.000252, 0.000000, 2 Model status : Optimal Objective value : 0.0000000000e+00 HiGHS run time : 0.00 julia> solution_summary(model) * Solver : HiGHS * Status Result count : 1 Termination status : OPTIMAL Message from the solver: "kHighsModelStatusOptimal" * Candidate solution (result #1) Primal status : FEASIBLE_POINT Dual status : FEASIBLE_POINT Objective value : 0.00000e+00 Objective bound : 0.00000e+00 Relative gap : Inf Dual objective value : 0.00000e+00 * Work counters Solve time (sec) : 3.03478e-04 Simplex iterations : 0 Barrier iterations : 0 Node count : -1
As well as the C calls:
julia> using HiGHS julia> model = Highs_create() Ptr{Nothing} @0x00007fab448a6c00 julia> Highs_addCol(model, 0.0, -Inf, Inf, 0, C_NULL, C_NULL) Running HiGHS 1.7.0 (git hash: 50670fd4c): Copyright (c) 2024 HiGHS under MIT licence terms 0 julia> Highs_addCol(model, 0.0, -Inf, Inf, 0, C_NULL, C_NULL) 0 julia> Highs_changeObjectiveSense(model, kHighsObjSenseMaximize) 0 julia> Highs_passHessian( model, 2, 1, kHighsHessianFormatTriangular, Cint[0, 1, 1], Cint[1], [1.0], ) 0 julia> Highs_run(model) Coefficient ranges: Cost [0e+00, 0e+00] Bound [0e+00, 0e+00] Iteration, Runtime, ObjVal, NullspaceDim 0, 0.000229, 0.000000, 2 2, 0.000256, 0.000000, 2 Model status : Optimal Objective value : 0.0000000000e+00 HiGHS run time : 0.00 0 julia> Highs_getModelStatus(model) 7
Originally reported in https://discourse.julialang.org/t/highs-jl-gives-strange-results/112995 x-ref jump-dev/HiGHS.jl#210
The text was updated successfully, but these errors were encountered:
This might be a side effect I didn't anticipate of a recent improvement I made for unconstrained QPs. I'll check
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feldmeier
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Solving
Max x * y
returns "Optimal" instead of declaring the QP to be non-convex. See the JuMP example:As well as the C calls:
Originally reported in https://discourse.julialang.org/t/highs-jl-gives-strange-results/112995
x-ref jump-dev/HiGHS.jl#210
The text was updated successfully, but these errors were encountered: