maxtime_cpu is not respected #295
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Use: minlp_solver = JuMP.optimizer_with_attributes(KNITRO.Optimizer, MOI.TimeLimitSec() => 30)We don't do anything special with parameters, so this might depend on the version of KNITRO that you have installed. |
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Thank you for the prompt response, Oscar! I included the time limit via MOI as you suggested. Here is the code I use now: However, it seems the 30-second time limit is not taken by the solver. I include the solver log below. And here is my versions information: Knitro: 13.0.1, KNITRO.jl: v0.11.1, JuMP.jl: v0.22.3, PowerModels.jl: v 0.19.10. Operating system: macOS Sonoma with M1 chip. |
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Interesting. It's useful to have an example that fails. This looks like an issue in the upstream KNITRO solver, because all we do here is pass the options. I'll take a look |
Wait. The most recent version of KNITRO.jl is v0.14.2. Can you try updating??? |
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Ah. I can't test this locally because I only have a limited size license I think this is just a bug in KNITRO julia> model = KNITRO.Optimizer();
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
julia> p = Ref{Cint}(0)
Base.RefValue{Int32}(0)
julia> KN_get_param_id(model.inner, "maxtime_cpu", p)
-521
julia> p
Base.RefValue{Int32}(0)
julia> KN_get_param_id(model.inner, "maxtimecpu", p)
0
julia> p
Base.RefValue{Int32}(1024)
julia> KN_set_double_param_by_name(model.inner, "maxtime_cpu", 30.0)
0
julia> KN_set_double_param_by_name(model.inner, "maxtimecpu", 30.0)
-516
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Thank you, Oscar! Is there a way to fix this bug in KNITRO.jl source code? |
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Can you try using JuMP, KNITRO, PowerModels
minlp_solver = JuMP.optimizer_with_attributes(KNITRO.Optimizer, MOI.TimeLimitSec() => 30.0)
solve_ots("pglib_opf_case24_ieee_rts__sad.m", ACPPowerModel, minlp_solver) |
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It seems the time limit is still not taken, after using the most updated KNITRO.jl version. After updating, I am now using the following packages: KNITRO.jl: v0.14.2, JuMP.jl: v1.22.2, PowerModels.jl: v0.21.2. I ran the following code (I reduced the time limit to 15 seconds): And here is the solver log, which does not seem to indicate that the time limit is taken: |
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What about: using JuMP, KNITRO, PowerModels
minlp_solver = JuMP.optimizer_with_attributes(KNITRO.Optimizer, "maxtime_real" => 15.0)We should probably contact Artelys support about this. |
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Can you check that any options work? julia> using JuMP, KNITRO, PowerModels
julia> minlp_solver = JuMP.optimizer_with_attributes(KNITRO.Optimizer, "outlev" => 0)
MathOptInterface.OptimizerWithAttributes(KNITRO.Optimizer, Pair{MathOptInterface.AbstractOptimizerAttribute, Any}[MathOptInterface.RawOptimizerAttribute("outlev") => 0])
julia> solve_ots("pglib_opf_case14_ieee__api.m", ACPPowerModel, minlp_solver)
[info | PowerModels]: removing 3 cost terms from generator 4: Float64[]
[info | PowerModels]: removing 1 cost terms from generator 1: [792.0951, 0.0]
[info | PowerModels]: removing 3 cost terms from generator 5: Float64[]
[info | PowerModels]: removing 1 cost terms from generator 2: [2326.9494, 0.0]
[info | PowerModels]: removing 3 cost terms from generator 3: Float64[]
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
Dict{String, Any} with 8 entries:
"solve_time" => 0.000871
"optimizer" => "Knitro"
"termination_status" => INTERRUPTED
"dual_status" => UNKNOWN_RESULT_STATUS
"primal_status" => UNKNOWN_RESULT_STATUS
"objective" => 0.0
"solution" => Dict{String, Any}("baseMVA"=>100.0, "branch"=>Dict{String, Any}("4"=>Dict{…
"objective_lb" => -1.79769e308 |
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The For And here is the log. The |
To clarify: this appears to be a problem with the upstream solver and not with KNITRO.jl. We don't do anything other than pass options straight through. |
odow
changed the title
MathOptInterface.UnsupportedAttribute Error when using maxtime_cpu
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I'm a member of Knitro development team, do not hesitate to contact us at |
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Thank you very much for the follow up. I tried both options, and for both of them, I encountered the error then I will get the error: And the same for |
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@Bougron, there does seem to be an issue with the C API: When getting the param ID, it requires julia> using KNITRO
julia> model = KNITRO.Optimizer();
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
julia> kc = model.inner;
julia> param_id = Ref{Cint}(0);
julia> KN_get_param_id(kc, "mip_maxtime_cpu", param_id)
-521
julia> param_id
Base.RefValue{Int32}(0)
julia> KN_get_param_id(kc, "mip_maxtimecpu", param_id)
0
julia> param_id
Base.RefValue{Int32}(2006)
julia> KN_set_double_param_by_name(kc, "mip_maxtime_cpu", 3.0)
0
julia> KN_set_double_param_by_name(kc, "mip_maxtimecpu", 3.0)
-516#297 works around this by using only the id version, so once merged, |
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Using #297, I get: julia> using JuMP, KNITRO, PowerModels
julia> minlp_solver = JuMP.optimizer_with_attributes(KNITRO.Optimizer, "mip_maxtimereal" => 0.0)
MathOptInterface.OptimizerWithAttributes(KNITRO.Optimizer, Pair{MathOptInterface.AbstractOptimizerAttribute, Any}[MathOptInterface.RawOptimizerAttribute("mip_maxtimereal") => 0.0])
julia> solve_ots("pglib_opf_case14_ieee__api.m", ACPPowerModel, minlp_solver)
[info | PowerModels]: removing 3 cost terms from generator 4: Float64[]
[info | PowerModels]: removing 1 cost terms from generator 1: [792.0951, 0.0]
[info | PowerModels]: removing 3 cost terms from generator 5: Float64[]
[info | PowerModels]: removing 1 cost terms from generator 2: [2326.9494, 0.0]
[info | PowerModels]: removing 3 cost terms from generator 3: Float64[]
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
##### This license is only intended for use by JuMP dev. #####
##### License is valid until Dec 31, 2024 #####
=======================================
Student License
(NOT FOR COMMERCIAL USE)
Artelys Knitro 13.1.0
=======================================
WARNING: Problem appears to have nonlinear equalities and be non-convex.
The Knitro mixed integer solver is designed for convex problems.
For non-convex problems it is only a heuristic, and the reported
bounds and optimality claims cannot be verified.
datacheck: 0
hessian_no_f: 1
numthreads: 1
mip_maxtime_real: 0
mip_numthreads: 1
Knitro changing mip_method from AUTO to 1.
Knitro changing mip_rootalg from AUTO to 1.
Knitro changing mip_lpalg from AUTO to 3.
Knitro changing mip_branchrule from AUTO to 2.
Knitro changing mip_selectrule from AUTO to 2.
Knitro changing mip_mir from AUTO to 1.
Knitro changing mip_rounding from AUTO to 3.
Knitro changing mip_heuristic_strategy from AUTO to 1.
Knitro changing mip_heuristic_feaspump from AUTO to 1.
Knitro changing mip_heuristic_misqp from AUTO to 0.
Knitro changing mip_heuristic_mpec from AUTO to 1.
Knitro changing mip_heuristic_diving from AUTO to 0.
Knitro changing mip_heuristic_lns from AUTO to 0.
Knitro changing mip_pseudoinit from AUTO to 1.
Problem Characteristics
-----------------------
Objective goal: Minimize
Objective type: linear
Number of variables: 138
bounded below only: 0
bounded above only: 0
bounded below and above: 121
fixed: 3
free: 14
Number of binary variables: 20
Number of integer variables: 0
Number of constraints: 189
linear equalities: 28
quadratic equalities: 1
gen. nonlinear equalities: 80
linear one-sided inequalities: 0
quadratic one-sided inequalities: 80
gen. nonlinear one-sided inequalities: 0
linear two-sided inequalities: 0
quadratic two-sided inequalities: 0
gen. nonlinear two-sided inequalities: 0
Number of nonzeros in Jacobian: 812
Number of nonzeros in Hessian: 302
Knitro detected 0 GUB constraints
Knitro derived 0 knapsack covers after examining 0 constraints
Knitro using Branch and Bound method with 1 thread.
Nodes Best solution Best bound Gap Time
Expl | Unexpl value value (secs)
--------------- ------------- ---------- --- ------
EXIT: Time limit reached. No integer feasible point found.
HINT: The problem may be a non-convex mixed-integer problem. Set
mip_multistart=1 to enable a mixed-integer multistart heuristic,
which may improve the chances of finding the global solution.
Final Statistics for MIP
------------------------
Final objective value =
Final bound value = 0.00000000000000e+00
Final optimality gap (abs / rel) = Infinity
# of nodes processed = 0 (0.000s)
# of strong branching evaluations = 0 (0.000s)
# of function evaluations = 2 (0.000s)
# of gradient evaluations = 1 (0.000s)
# of hessian evaluations = 0 (0.000s)
# of hessian-vector evaluations = 0
# of subproblems processed = 0 (0.000s)
Total program time (secs) = 0.00067 (0.001 CPU time)
Time spent in evaluations (secs) = 0.00016
Cuts statistics (computed / added)
----------------------------------
Knapsack cuts = 0 / 0
Mixed-Integer Rounding cuts = 0 / 0
Heuristics statistics (calls / successes / time)
------------------------------------------------
Feasibility pump = 0 / 0 / 0.000s
Rounding heuristic = 0 / 0 / 0.000s
MPEC heuristic = 0 / 0 / 0.000s
===========================================================================
Dict{String, Any} with 8 entries:
"solve_time" => 0.00072
"optimizer" => "Knitro"
"termination_status" => TIME_LIMIT
"dual_status" => INFEASIBLE_POINT
"primal_status" => INFEASIBLE_POINT
"objective" => 0.0
"solution" => Dict{String, Any}("baseMVA"=>100.0, "branch"=>Dict{String, Any}("4"=>Dict{…
"objective_lb" => 0.0so it is working. @Bougron, as a secondary request then, shouldn't |
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Yes this is expected (even though I understand it is confusing), the documentation mentions it in the description: |
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Regarding the naming, we are checking it out (mip_maxtimecpu vs mip_maxtime_cpu). |
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Ah, then perhaps all that is needed is that for the documentation of I see that other options have this wording, but it is missing from the |
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This will be fixed when I release #301 |
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This bug is similar to the one mentioned here: https://discourse.julialang.org/t/julia-with-knitro/81686.
A MWE is as follows:
The data file
pglib_opf_case24_ieee_rts__sad.mis attached below (drop the extension.txtbefore running).The code runs fine if one does not set the
maxtime_cpuparameter in attributes, so it seems to be an issue with KNITRO.jl/MOI not being able to talk the parameter.pglib_opf_case24_ieee_rts__sad.m.txt
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