zolanaj
commented
10 months ago cc @odow
Open zolanaj opened 10 months ago
zolanaj
commented
10 months ago cc @odow
odow
commented
10 months ago I've a bit limited debugging this because I only have the community license, and this problem is too big, but...
In JuMP's Objective value : 3.56703e+07 output, we're querying:
There's not a lot to go wrong here, so if this doesn't return the optimal solution, but the first solution from
k 35670343.87 33552689.03 1 5.then it seems that this is a bug in Xpress. (Unless we need to set some options for returning multiple solutions?)
Here's the MPS file that Maddie sent me via email: problematic_mps.mps.zip
Could you:
Provide the output of versioninfo()
Provide the versions of Xpress that you tried (9.2 buggy, others not so?)
Try running with heuristics turned off JuMP.set_attribute(model, "HEUREMPHASIS", 0)
Confirm that we can reproduce this outside of REopt with just the MPS file.
import JuMP, Xpress
model = JuMP.read_from_file("problematic_mps.mps")
JuMP.set_optimizer(model, Xpress.Optimizer)
JuMP.set_attribute(model, "MIPRELSTOP", 0.01) # Or whatever option you set?
JuMP.optimize!(model)
JuMP.solution_summary(model)So this doesn't seem related to multiple solutions, because there's a special set of functions for that:
So I'm going to guess that this is a bug in Xpress.
odow
commented
5 months ago @joaquimg could you try reproducing this? The community license is too small.
odow
commented
4 months ago So now that I've spent a bit of time in the code, I really think this is an upstream issue. I can't see how this would be a bug in Xpress.jl.
joaquimg
commented
4 months ago I ran the basic thing it was taking forever:
julia> import JuMP, Xpress
julia> model = JuMP.read_from_file("problematic_mps.mps")
A JuMP Model
Minimization problem with:
Variables: 315397
Objective function type: JuMP.AffExpr
`JuMP.AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 87604 constraints
`JuMP.AffExpr`-in-`MathOptInterface.GreaterThan{Float64}`: 61339 constraints
`JuMP.AffExpr`-in-`MathOptInterface.LessThan{Float64}`: 105137 constraints
`JuMP.VariableRef`-in-`MathOptInterface.EqualTo{Float64}`: 43801 constraints
`JuMP.VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 254073 constraints
`JuMP.VariableRef`-in-`MathOptInterface.ZeroOne`: 17523 constraints
Model mode: AUTOMATIC
CachingOptimizer state: NO_OPTIMIZER
Solver name: No optimizer attached.
julia> JuMP.set_optimizer(model, Xpress.Optimizer)
julia> JuMP.set_attribute(model, "MIPRELSTOP", 0.01) # Or whatever option you set?
julia> JuMP.optimize!(model)
FICO Xpress v9.1.0, Hyper, solve started 13:21:25, Apr 10, 2024
Heap usage: 85MB (peak 85MB, 72KB system)
Minimizing MILP using up to 8 threads and up to 15GB memory, with these control settings:
OUTPUTLOG = 1
MPSNAMELENGTH = 64
CALLBACKFROMMASTERTHREAD = 1
MIPRELSTOP = .01
Original problem has:
254080 rows 315397 cols 837299 elements 17523 entities
Presolved problem has:
118895 rows 78496 cols 419614 elements 8763 entities
Presolve finished in 2 seconds
Heap usage: 137MB (peak 298MB, 72KB system)
Coefficient range original solved
Coefficients [min,max] : [ 9.97e-05, 1.00e+12] / [ 1.40e-04, 1.49e+04]
RHS and bounds [min,max] : [ 1.00e+00, 1.00e+14] / [ 5.98e-04, 2.50e+12]
Objective [min,max] : [ 1.14e-04, 1.51e+04] / [ 1.08e-04, 2.92e+10]
Autoscaling applied Curtis-Reid scaling
Symmetric problem: generators: 431, support set: 432
Number of orbits: 2, largest orbit: 432
Row orbits: 3, row support: 1296
Will try to keep branch and bound tree memory usage below 5.8GB
Starting concurrent solve with dual (1 thread) and barrier (7 threads)
Concurrent-Solve, 2s
Dual Barrier
objective dual inf p.obj. d.obj.
D 3889143.2 .0000000 | B -1.549E+21 40745228.
D 4486696.4 .0000000 | B -1.228E+20 -2.704E+19
D 6333675.2 .0000000 | B -7.017E+17 -3.763E+15
D 8299850.7 .0000000 | B -7.499E+15 1.945E+15
D 9805099.7 .0000000 | B -1.028E+09 5.558E+09
D 11576278. .0000000 | B 24101024. 50274176.
D 12609770. .0000000 | B 32900675. 33795727.
D 13218450. .0000000 | B 33381914. 33486821.
D 13317250. .0000000 | B 33446195. 33446811.
D 14755373. .0000000 | crossover
----- interrupted ------ | ------- optimal --------
Concurrent statistics:
Dual: 31832 simplex iterations, 5.13s
Barrier: 62 barrier and 28543 simplex iterations, 5.10s
Barrier used 7 threads 4 cores, L1\L2 cache: 48K\12288K
Barrier used AVX support, crossover used 7 threads
Optimal solution found
Its Obj Value S Ninf Nneg Sum Inf Time
1 33446472.64 P 0 0 .000000 7
Barrier solved problem
62 barrier and 28543 simplex iterations in 5.18 seconds at time 7
Final objective : 3.344647264049235e+07
Max primal violation (abs/rel) : 9.417e-10 / 5.056e-13
Max dual violation (abs/rel) : 3.553e-15 / 1.776e-15
Max complementarity viol. (abs/rel) : 0.0 / 0.0
High attention level predicted from matrix features
Starting root cutting & heuristics
Deterministic mode with up to 1 additional thread
Its Type BestSoln BestBound Sols Add Del Gap GInf Time
k 35578106.66 33446472.64 1 5.99% 0 21
Heuristic search 'R' started
Heuristic R running (50000 LP iterations in 8.6 seconds)
Heuristic search 'R' stopped
Heuristic M running (50000 LP iterations in 931.1 seconds)Then a I ran with HEUREMPHASIS = 0 got:
julia> import JuMP, Xpress
julia> model = JuMP.read_from_file("problematic_mps.mps")
A JuMP Model
Minimization problem with:
Variables: 315397
Objective function type: JuMP.AffExpr
`JuMP.AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 87604 constraints
`JuMP.AffExpr`-in-`MathOptInterface.GreaterThan{Float64}`: 61339 constraints
`JuMP.AffExpr`-in-`MathOptInterface.LessThan{Float64}`: 105137 constraints
`JuMP.VariableRef`-in-`MathOptInterface.EqualTo{Float64}`: 43801 constraints
`JuMP.VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 254073 constraints
`JuMP.VariableRef`-in-`MathOptInterface.ZeroOne`: 17523 constraints
Model mode: AUTOMATIC
CachingOptimizer state: NO_OPTIMIZER
Solver name: No optimizer attached.
julia> JuMP.set_optimizer(model, Xpress.Optimizer)
julia> JuMP.set_attribute(model, "MIPRELSTOP", 0.01) # Or whatever option you set?JuMP.set_attribute(model, "HEUREMPHASIS", 0)
julia> JuMP.set_attribute(model, "HEUREMPHASIS", 0)
julia> JuMP.optimize!(model)
FICO Xpress v9.1.0, Hyper, solve started 13:43:46, Apr 10, 2024
Heap usage: 85MB (peak 85MB, 72KB system)
Minimizing MILP using up to 8 threads and up to 15GB memory, with these control settings:
OUTPUTLOG = 1
MPSNAMELENGTH = 64
CALLBACKFROMMASTERTHREAD = 1
HEUREMPHASIS = 0
MIPRELSTOP = .01
Original problem has:
254080 rows 315397 cols 837299 elements 17523 entities
Presolved problem has:
118895 rows 78496 cols 419614 elements 8763 entities
Presolve finished in 2 seconds
Heap usage: 137MB (peak 298MB, 72KB system)
Coefficient range original solved
Coefficients [min,max] : [ 9.97e-05, 1.00e+12] / [ 1.40e-04, 1.49e+04]
RHS and bounds [min,max] : [ 1.00e+00, 1.00e+14] / [ 5.98e-04, 2.50e+12]
Objective [min,max] : [ 1.14e-04, 1.51e+04] / [ 1.08e-04, 2.92e+10]
Autoscaling applied Curtis-Reid scaling
Symmetric problem: generators: 431, support set: 432
Number of orbits: 2, largest orbit: 432
Row orbits: 3, row support: 1296
Will try to keep branch and bound tree memory usage below 6.5GB
Starting concurrent solve with dual (1 thread) and barrier (7 threads)
Concurrent-Solve, 3s
Dual Barrier
objective dual inf p.obj. d.obj.
D 3889143.2 .0000000 | B -1.549E+21 40745228.
D 4486696.4 .0000000 | B -1.228E+20 -2.704E+19
D 6333675.2 .0000000 | B -7.017E+17 -3.763E+15
D 8299850.7 .0000000 | B -7.499E+15 1.945E+15
D 9805099.7 .0000000 | B -1.028E+09 5.558E+09
D 11576278. .0000000 | B 24101024. 50274176.
D 12609770. .0000000 | B 32900675. 33795727.
D 13218450. .0000000 | B 33381914. 33486821.
D 13317250. .0000000 | B 33446195. 33446811.
D 14755373. .0000000 | crossover
----- interrupted ------ | ------- optimal --------
Concurrent statistics:
Dual: 31654 simplex iterations, 6.78s
Barrier: 62 barrier and 28543 simplex iterations, 6.75s
Barrier used 7 threads 4 cores, L1\L2 cache: 48K\12288K
Barrier used AVX support, crossover used 7 threads
Optimal solution found
Its Obj Value S Ninf Nneg Sum Inf Time
1 33446472.64 P 0 0 .000000 9
Barrier solved problem
62 barrier and 28543 simplex iterations in 6.84 seconds at time 9
Final objective : 3.344647264049235e+07
Max primal violation (abs/rel) : 9.417e-10 / 5.056e-13
Max dual violation (abs/rel) : 3.553e-15 / 1.776e-15
Max complementarity viol. (abs/rel) : 0.0 / 0.0
High attention level predicted from matrix features
Starting root cutting & heuristics
Its Type BestSoln BestBound Sols Add Del Gap GInf Time
* 33446472.64 33446472.64 1 0.00% 0 10
*** Search completed ***
Uncrunching matrix
Final MIP objective : 3.344647264049235e+07
Final MIP bound : 3.344647264049235e+07
Solution time / primaldual integral : 10.17s/ 99.803440%
Number of solutions found / nodes : 1 / 1
Max primal violation (abs/rel) : 9.095e-13 / 9.077e-13
Max integer violation (abs ) : 1.818e-07
Refined MIP solution (0.0 fractionality 6.812e-13 abs infeasibility)
julia> JuMP.solution_summary(model)
* Solver : Xpress
* Status
Result count : 1
Termination status : OPTIMAL
Message from the solver:
"6 Global search complete - integer solution found ( XPRS_MIP_OPTIMAL). - no interruption - the solve completed normally"
* Candidate solution (result #1)
Primal status : FEASIBLE_POINT
Dual status : NO_SOLUTION
Objective value : 3.55781e+07
Objective bound : 3.34465e+07
Relative gap : 5.99142e-02
Dual objective value : 3.55781e+07
* Work counters
Solve time (sec) : 2.50390e+01
We encountered a difference between the best found solution in the solver log for Xpress 9.2:
And what's in the the solution summary for our instance (copy-pasted from the REPL):
It appears to return the first solution found instead of the optimal solution for our MILP.