jump-dev/gurobi.jl

A Julia interface to the Gurobi Optimizer

gurobi.jl's Issues

Unable to set Integer options to infinity

Because Inf is floating point, this code in grb_params.jl fails when trying to set something in GRB_INT_PARAMS to infinity.

function set_int_param!(env::Env, name::ASCIIString, v::Integer)
ret = @grb_ccall(setintparam, Cint, (Ptr{Void}, Ptr{Cchar}, Cint),
env, name, v)
if ret != 0
throw(GurobiError(env, ret))
end
end

Support in addvars! for SparseMatrixCSC

I am trying to use the Gurobi.jl interface to solve an LP (min c'x s.t. Ax == b) with parameters c, A, and b all of type SparseMatrixCSC{Float64,Int64}. I simulate them as follows:

m = 5000    # nrows
n = 10000  # ncols
s = 0.01    # sparsity level
A = sprandn(m,n,s)
c = sprand(m,1,s)
y = sprandn(n,1,s)
x = sparsevec(y.rowval,max(y.nzval,0.0),y.m)
b = A*x + sprand(m,1,s)

I match the Gurobi variable names: f == c, Aeq == A, and beq == b.

addvars! throws an error if I feed it a sparse vector f. Does the Gurobi solver not admit sparse parameters for solving big LPs?

Note that I may not be simulating my LP parameters intelligently; having a sparse f may not make sense in the real world (and if it is not, please correct me!)

Gurobi v0.3.0 does not compile on julia0.6.0-alpha win64 due to bug on grb_ccall

The issues is the same as the one in this topic

and commented in: #71

Q_NOT_PSD is a possible return from get_status_code

using JuMP
using Gurobi

m = Model(solver=GurobiSolver())

@defVar(m, x)
@defVar(m, u[1:3])
@defVar(m, y[1:2], Bin)

u_samps = [0.0 0.0 0.0;
           1.0 1.0 1.0]
x_samps = [5.0, 20.0]

@addConstraint(m, x == x_samps[1]*y[1] + x_samps[2]*y[2])

addConstraint(m, sum([(u_samps[1,k]^2 - u_samps[1,k]*u[k] + u[k]^2) for k=1:3]) + y[1] >= 1)
addConstraint(m, sum([(u_samps[2,k]^2 - u_samps[2,k]*u[k] + u[k]^2) for k=1:3]) + y[2] >= 1)

solve(m)

println(getValue(x))

gives

ERROR: BoundsError()
 in get_status at /home/idunning/.julia/v0.3/Gurobi/src/grb_solve.jl:61

because get_status_code(model) actually returns an error code, Q_NOT_PSD (10022) which is of course not a solve code... strange logic.

remove lp_model?

@lindahua, do you mind if lp_model is removed in favor of linprog in MathProgBase? Although the interfaces are not identical, supporting both matlab-type interfaces seems redundant, and any convenience versions (like providing a separate Aeq and Aineq) should be build on top of linprog so that they are solver independent.

qp_model should stay for now, since we don't yet have QP support in MathProgBase.

tests are failing

On master, Gurobi 7.0.1:

Unbounded model
Passed
ERROR: LoadError: LoadError:     You have encountered a known bug in Gurobi. Any information you query from the model may be incorrect.
    This bug has existed since the first version of Gurobi but is fixed in Gurobi v7.0.

    For more information go to https://github.com/JuliaOpt/Gurobi.jl/issues/60.
    Please leave a comment stating that you encountered this bug! We would like to know how prevalent it is.

 in updatemodel!(::Gurobi.GurobiMathProgModel) at /home/mlubin/.julia/v0.5/Gurobi/src/GurobiSolverInterface.jl:251
 in optimize!(::Gurobi.GurobiMathProgModel) at /home/mlubin/.julia/v0.5/Gurobi/src/GurobiSolverInterface.jl:326
 in linprogsolvertest(::Gurobi.GurobiSolver, ::Float64) at /home/mlubin/.julia/v0.5/MathProgBase/test/linproginterface.jl:274
 in linprogsolvertest(::Gurobi.GurobiSolver) at /home/mlubin/.julia/v0.5/MathProgBase/test/linproginterface.jl:7
 in include_from_node1(::String) at ./loading.jl:488
 in evalfile(::String, ::Array{String,1}) at ./loading.jl:504
 in macro expansion; at /home/mlubin/.julia/v0.5/Gurobi/test/runtests.jl:20 [inlined]
 in anonymous at ./<missing>:?
 in include_from_node1(::String) at ./loading.jl:488
 in process_options(::Base.JLOptions) at ./client.jl:265
 in _start() at ./client.jl:321
while loading /home/mlubin/.julia/v0.5/Gurobi/test/mathprog.jl, in expression starting on line 10
while loading /home/mlubin/.julia/v0.5/Gurobi/test/runtests.jl, in expression starting on line 17

Any idea @odow @joaquimg?

GUROBI_HOME not found despite correct environment variable

Hi All,

I believe I have set the correct environment variables to point toward my Gurobi installation, yet the installation of Gurobi.jl is still failing. See here:

[msl33@percent bin]$ echo $GUROBI_HOME
/home/grad/msl33/gurobi751/linux64
[msl33@percent bin]$ ./julia
               _
   _       _ _(_)_     |  A fresh approach to technical computing
  (_)     | (_) (_)    |  Documentation: https://docs.julialang.org
   _ _   _| |_  __ _   |  Type "?help" for help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 0.6.0 (2017-06-19 13:05 UTC)
 _/ |\__'_|_|_|\__'_|  |  Official http://julialang.org/ release
|__/                   |  x86_64-pc-linux-gnu

julia> Pkg.add("Gurobi")
INFO: Installing Gurobi v0.3.2
INFO: Building Gurobi
============================================[ ERROR: Gurobi ]============================================

LoadError: Unable to locate Gurobi installation. Note that this must be downloaded separately from gurobi.com
while loading /home/grad/msl33/.julia/v0.6/Gurobi/deps/build.jl, in expression starting on line 42

=========================================================================================================

============================================[ BUILD ERRORS ]=============================================

WARNING: Gurobi had build errors.

 - packages with build errors remain installed in /home/grad/msl33/.julia/v0.6
 - build the package(s) and all dependencies with `Pkg.build("Gurobi")`
 - build a single package by running its `deps/build.jl` script

=========================================================================================================
INFO: Package database updated
INFO: METADATA is out-of-date \u2014 you may not have the latest version of Gurobi
INFO: Use `Pkg.update()` to get the latest versions of your packages

julia> 

[msl33@percent bin]$ gurobi.sh
Python 2.7.13 (default, Jun  8 2017, 07:12:38) 
[GCC 4.4.7 20120313 (Red Hat 4.4.7-18)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
Academic license - for non-commercial use only

Gurobi Interactive Shell (linux64), Version 7.5.1
Copyright (c) 2017, Gurobi Optimization, Inc.
Type "help()" for help

gurobi> 

As far as I can tell the GUROBI_HOME environment variable is set correctly. Please help.

Gurobi addconstr! only adds constraint in solver, but not in GurobiMathProgModel

I'm fairly new to the whole JuMP/MathProgBase modelling environment and I, therefore, might have misunderstood the whole architecture which might be the main problem.

My problem is:
When I add constraints it seems like they are only added in the Gurobi Solver and not in the GurobiMathProgModel.
How can I update my GurobiMathProgModel after I added the constraints?

My process is the following:

1. I build a JuMP model (as it is the easiest way to model) and convert it to a GurobiMathProgModel, as I need to change the coefficients later in the script.
2. I then later need to add additional constraints to my problem and send this GurobiMathProgModel to different functions in my script.

I put some example code below that reflects my problem.
I hope you can help me or explain how I should actually use the architecture.

m = Model(solver = GurobiSolver())

#Add binary variables to JuMP model
@variable(m, 0 <= z[1:nCols] <= 1, Bin )

#Define objective function
@objective(m, Max, sum(z[i] for i=1:length(z)))

#Build model
JuMP.build(m)

#Convert to GurobiMathProgModel
m2 = internalmodel(m)

#Try to add constraint
Gurobi.addconstr!(m2, [1], [1], -Inf, 2)

#Updating model
Gurobi.updatemodel!(m2)

#Output GurobiMathProgModel to check number of constraints in the model
m2     #Output 0 constraints

#Get raw solver to check number of constraints
Gurobi.getrawsolver(m2) #Output 1 constraint

Installation using Pkg.add() Fails on Ubuntu

I'm unable to install Gurobi with:

Pkg.add("Gurobi")

I get the following output:

===============================[ ERROR: Gurobi ]================================

Unable to locate Gurobi installation. Note that this must be downloaded separately from gurobi.com
while loading /home/jtheurer/.julia/v0.3/Gurobi/deps/build.jl, in expression starting on line 36

================================================================================

================================[ BUILD ERRORS ]================================

WARNING: Gurobi had build errors.

 - packages with build errors remain installed in /home/jtheurer/.julia/v0.3
 - build the package(s) and all dependencies with `Pkg.build("Gurobi")`
 - build a single package by running its `deps/build.jl` script

================================================================================

I'm running 0.3.7 of julia

$ dpkg -s julia|grep "Version"
Version: 0.3.7-trusty1

Bug in GurobiSolverInterface.jl/getconstrsolution

I've been using your wonderful Gurobi wrapper with JuMP and MathProgBase for a few months now and it's been an absolute joy, and today I think I found a small bug in getconstrsolution. When a constraint is not tight, getconstrsolution returns a value that is not within constraint bounds.
For instance, the first half of the following code fails, while the second does not:

# getconstrsolutionTest.jl

using JuMP, MathProgBase, Gurobi

# Slack GEQ constraint
m = Model(solver=GurobiSolver())
@defVar(m, x)
@addConstraint(m, x >= 0)
@addConstraint(m, x >= 3)
@setObjective(m, Min, x)

buildInternalModel(m)
im = getInternalModel(m)

MathProgBase.optimize!(im)

for i = 1:length(MathProgBase.getconstrLB(im))
    println("Checking constraint $i")
    @assert MathProgBase.getconstrLB(im)[i] <= MathProgBase.getconstrsolution(im)[i] <= MathProgBase.getconstrUB(im)[i]
end

# Slack LEQ constraint
m = Model(solver=GurobiSolver())
@defVar(m, x)
@addConstraint(m, x <= 3)
@addConstraint(m, x <= 0)
@setObjective(m, Max, x)

buildInternalModel(m)
im = getInternalModel(m)

MathProgBase.optimize!(im)

for i = 1:length(MathProgBase.getconstrLB(im))
    println("Checking constraint $i")
    @assert MathProgBase.getconstrLB(im)[i] <= MathProgBase.getconstrsolution(im)[i] <= MathProgBase.getconstrUB(im)[i]
end

I think this is because the variables that represent slackness of a constraint might have an overall sign, which leads to a sign error on line 264 of GurobiSolverInterface.jl. Is this correct ?

Thanks for your help !

MathProgBase API updates

Opening this to keep track of adopting the new API changes in MathProgBase

handling range constraints in mathprog interface

The gurobi function addrangeconstrs introduces an additional slack variable to the problem for each constraint added. To properly support this, we need to transform user-facing variable indices to Gurobi variable indices at the mathprog interface layer (or convince Gurobi to make this transparent at the C-interface level). Until then, I'm printing a appropriate warning when range constraints are used.

Crash in getlibversion on Win32

grb_common::getlibversion crashes on win32.

Localized here:

julia> ccall( (:GRBversion, "gurobi51"), Void, (Ptr{Cint}, Ptr{Cint}, Ptr{Cint}), _major,_minor, _tech) 

(crashes). Observed on two different computers during @mlubin presentation today.

Gurobi throwing exception for attribute 'NumVars' after adding info callback

We are facing problem with Gurobi callback, which throws - ErrorException("optimizing: Gurobi.GurobiError(10017,\"Unable to retrieve attribute 'NumVars'\")". We commented grb_callback.jl:145 and rebuild the package, which makes it work.
We tried to execute the example, which is also throwing the same error.
Please find below the code.

using JuMP
using MathProgBase
using Gurobi

m = Model(solver = GurobiSolver(MIPGap=0.1, Cuts=0, VarBranch=1, TimeLimit=3600, OutputFlag=1))

@variable(m, 0 <= x <= 2, Int)
@variable(m, 0 <= y <= 2, Int)

@objective(m, Max, x + 2y)

@constraint(m, y + x <= 3.5)

type NodeData
    time::Float64  # in seconds since the epoch
    node::Int
    obj::Float64
    bestbound::Float64
end

bbdata = NodeData[]

function infocallback(cb)
    node      = MathProgBase.cbgetexplorednodes(cb)
    obj       = MathProgBase.cbgetobj(cb)
    bestbound = MathProgBase.cbgetbestbound(cb)
    push!(bbdata, NodeData(time(),node,obj,bestbound))
end
addinfocallback(m, infocallback, when = :Intermediate)

solve(m)

Library Used: Julia, JuMP
JuMP.jl Version: 0.17.1
Gurobi.jl Version: 0.3.3

Language and Solver
Julia Version: 0.5.1
Gurobi Version: 7.0.2

Crossover=0 not being respected

Will try to make test case, but any ideas why?

Deleting constraint

I sometimes want to remove a constraint to replace it by a different constraint not on the same variable. Here's a toy example that works:

using JuMP
using Gurobi

m = Model(solver=GurobiSolver(MIPFocus = 3))
x = @variable(m)
y = @variable(m)
con = @constraint(m, x<=1)
@constraint(m, x>=0)
@constraint(m, y>=2)
@objective(m, Min, (y-x)^2)
solve(m)
JuMP.setRHS(con, 100) # effectively deleting constraint
solve(m)

Unfortunately, this only works because I can choose a large number for JuMP.setRHS where I do not expect the constraint to be binding. Attempting JuMP.setRHS(con, Inf) leads to the following error message:

ERROR: LoadError: Internal error.
Stacktrace:
 [1] updatemodel!(::Gurobi.GurobiMathProgModel) at /home/vtjeng/.julia/v0.6/Gurobi/src/GurobiSolverInterface.jl:310
 [2] setvartype!(::Gurobi.GurobiMathProgModel, ::Array{Symbol,1}) at /home/vtjeng/.julia/v0.6/Gurobi/src/GurobiSolverInterface.jl:459
 [3] #build#119(::Bool, ::Bool, ::JuMP.ProblemTraits, ::Function, ::JuMP.Model) at /home/vtjeng/.julia/v0.6/JuMP/src/solvers.jl:391
 [4] (::JuMP.#kw##build)(::Array{Any,1}, ::JuMP.#build, ::JuMP.Model) at ./<missing>:0
 [5] #solve#116(::Bool, ::Bool, ::Bool, ::Array{Any,1}, ::Function, ::JuMP.Model) at /home/vtjeng/.julia/v0.6/JuMP/src/solvers.jl:168
 [6] solve(::JuMP.Model) at /home/vtjeng/.julia/v0.6/JuMP/src/solvers.jl:150
 [7] include_from_node1(::String) at ./loading.jl:569
 [8] include(::String) at ./sysimg.jl:14
 [9] process_options(::Base.JLOptions) at ./client.jl:305
 [10] _start() at ./client.jl:371

Is there any way I can work around this?

copy(model::Model) does not copy the solution information

If I create the model and then optimize it, Then I copy it with function copy(model::Model), I cannot get solution or basis from the copy of model but I can get from the original model.

Segfault in JuMP tests on Gurobi 6.5

With JuMP/Gurobi.jl master on OSX, Gurobi 6.5 is segfaulting in the callback.jl tests of JuMP.

Relevant test code:

using JuMP, Gurobi, FactCheck
entered = [false,false]
mod = Model(solver=GurobiSolver(Presolve=0))
@defVar(mod, 0 <= x <= 2, Int)
@defVar(mod, 0 <= y <= 2, Int)
@setObjective(mod, Max, y + 0.5x)
function corners(cb)
    x_val = getValue(x)
    y_val = getValue(y)
    TOL = 1e-6
    # Check top right
    if y_val + x_val > 3 + TOL
        @addLazyConstraint(cb, y + 0.5x + 0.5x <= 3)
    end
    entered[1] = true
    @fact_throws ErrorException @defVar(cb, z)
    @fact_throws ErrorException @addLazyConstraint(cb, x^2 <= 1)
end
addLazyCallback(mod, corners)
addLazyCallback(mod, cb -> (entered[2] = true))
@fact solve(mod) --> :Optimal

gives

Optimize a model with 0 rows, 2 columns and 0 nonzeros
Coefficient statistics:
  Matrix range    [0e+00, 0e+00]
  Objective range [5e-01, 1e+00]
  Bounds range    [2e+00, 2e+00]
  RHS range       [0e+00, 0e+00]
Variable types: 0 continuous, 2 integer (0 binary)
[1]    899 segmentation fault  julia --color=yes

It works using Gurobi 6.0.5. @yeesian can reproduce it as well, something funny going on with callbacks?

Warnings in Pkg.build("Gurobi") with Julia v0.5

There's a deprecation warning, but then it stops building, but it still works (sorry for my impatience.)

julia> Pkg.status("Gurobi")
 - Gurobi                        0.2.4

julia> Pkg.build("Gurobi")
INFO: Building Gurobi
WARNING: `@unix_only` is deprecated, use `@static if is_unix()` instead
 in depwarn(::String, ::Symbol) at ./deprecated.jl:64
 in @unix_only(::Any) at ./deprecated.jl:492
 in include_from_node1(::String) at ./loading.jl:488
 in evalfile(::String, ::Array{String,1}) at ./loading.jl:504 (repeats 2 times)
 in cd(::##2#4, ::String) at ./file.jl:59
 in (::##1#3)(::IOStream) at ./none:13
 in open(::##1#3, ::String, ::String) at ./iostream.jl:113
 in eval(::Module, ::Any) at ./boot.jl:234
 in process_options(::Base.JLOptions) at ./client.jl:239
 in _start() at ./client.jl:318
while loading /home/bzfschwa/.julia/v0.5/Gurobi/deps/build.jl, in expression starting on line 16

julia> versioninfo()
Julia Version 0.5.0
Commit 3c9d753 (2016-09-19 18:14 UTC)
Platform Info:
  System: Linux (x86_64-pc-linux-gnu)
  CPU: Intel(R) Core(TM) i7-3520M CPU @ 2.90GHz
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Sandybridge)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.7.1 (ORCJIT, ivybridge)

Gurobi not installing correctly on OSX

Hi Gurobi,

I'm new to Julia and trying to install Gurobi.jl. I can add it and Pkg.build("Gurobi") completes successfully, but when I try to use it, it tells me to run Pkg.build again.

julia> Pkg.add("Gurobi")
INFO: Installing Gurobi v0.1.25
INFO: Building Gurobi
INFO: Package database updated

julia> Pkg.build("Gurobi")
INFO: Building Gurobi

julia> using Gurobi
ERROR: Gurobi not properly installed. Please run Pkg.build("Gurobi")
 in error at error.jl:21
 in include at /Applications/Julia-0.3.6.app/Contents/Resources/julia/lib/julia/sys.dylib
 in include_from_node1 at /Applications/Julia-0.3.6.app/Contents/Resources/julia/lib/julia/sys.dylib
 in reload_path at loading.jl:152
 in _require at loading.jl:67
 in require at loading.jl:51
while loading /Users/ryangiordanonon-admin/.julia/v0.3/Gurobi/src/Gurobi.jl, in expression starting on line 6

julia> Pkg.build("Gurobi")
INFO: Building Gurobi

julia> 

Pkg.test("Gurobi") also fails:

julia> Pkg.test("Gurobi")
INFO: Testing Gurobi
running lp_01a.jl ...
ERROR: Gurobi not properly installed. Please run Pkg.build("Gurobi")
 in error at error.jl:21
 in include at /Applications/Julia-0.3.6.app/Contents/Resources/julia/lib/julia/sys.dylib

Thanks in advance for your help,
Ryan

Not Freeing Gurobi Environment Between Calculations

Background

We are using Gurobi.jl with JuMP.jl to run calculations. In a given script, we will run ~100 models. Rather than run the calculations locally, the Gurobi model connects to a Gurobi computation server. (If you're unfamiliar - the only change locally is that the license file says "instead of a license key, I actually point to a server". Everything else is basically the same).

Issue

When running the script, calculations are blocked until they complete on the server. However, when the calculation appears to have completed locally (because it receives a convergent result) - the computation server still shows it as a running calculation. The calculation is not consuming any resources, but it blocks additional calculations and causes the next calculation to block. So, if we limit the computation server to 2 simultaneous calculations - then two begin processing, finish, but continue to block, and all subsequent calculations enter a queued state. They do not get calculated until the original calculations time out.

Proposed Fix

Can we explicitly free the Gurobi environment after a calculation completes? Is there a way to explicitely do this using the JuMP interface?

Debugging

If you need a computation server for testing, I can spin one up - ping me (philip at staffjoy.com)

Gurobi Support Input

We have different APIs from which you can call Gurobi (C, C++, Java, Python,...). In some of these APIs there are explicit methods for freeing a Gurobi environment, in some of them you just delete the GRBEnv object. If you are not using one of our APIs there is no way to free the environment except for killing the complete process.

As you are using Julia JuMP for calling Gurobi, I don't see a way for you do free the environment, except for changing the JuMP code. If this is what you want to do, just tell me which API they use (I guess C or C++, for C there is a function called GRBfreeEnv: http://www.gurobi.com/documentation/6.0/refman/c_grbfreeenv.html).

Our complete documentation can be found here: http://www.gurobi.com/documentation/
There are also reference manuals for the different programming languages.

Segfault on ctrl-c

Is it possible to give Gurobi the same magic as jump-dev/CPLEX.jl#45 so that it doesn't segfault on ctrl-c? I'm happy to have a go if needed, but it might be easier for someone that understands the internals better than I do.

Related, I've been working with a model given to me that uses gurobipy, and on that, ctrl-c interrupts the solve and returns the current incumbent. I'm not sure if that would fall out here as a consequence, but it would be pretty cool if it worked!

get_basis limit issue

I think there is a bug with function get_basis(model::Model). It is not accounting for slack variables, the limit shouldn't be num_vars(model) but the number of lines of A matrix. After, it has to use GRBgetBasisHead to know the corresponding variables and known which variables are slacks. I will try to submit pull request soon.

error compiling #GurobiMathProgModel#10: error compiling Type: could not load library "gurobi75"

Hi all,

I tried to solve an IP with JuMP using Gurobi. Yet I get an error:

julia> status=solve(m)
ERROR: error compiling #GurobiMathProgModel#10: error compiling Type: could not
load library "gurobi75"
The specified module could not be found.

Stacktrace:
[1] (::Core.#kw#Type)(::Array{Any,1}, ::Type{Gurobi.GurobiMathProgModel}, ::Voi
d) at .<missing>:0
[2] LinearQuadraticModel(::Gurobi.GurobiSolver) at C:\Users\Steffie.julia\v0.6
\Gurobi\src\GurobiSolverInterface.jl:68
[3] #build#119(::Bool, ::Bool, ::JuMP.ProblemTraits, ::Function, ::JuMP.Model)
at C:\Users\Steffie.julia\v0.6\JuMP\src\solvers.jl:356
[4] (::JuMP.#kw##build)(::Array{Any,1}, ::JuMP.#build, ::JuMP.Model) at .<miss
ing>:0
[5] #solve#116(::Bool, ::Bool, ::Bool, ::Array{Any,1}, ::Function, ::JuMP.Model
) at C:\Users\Steffie.julia\v0.6\JuMP\src\solvers.jl:168
[6] solve(::JuMP.Model) at C:\Users\Steffie.julia\v0.6\JuMP\src\solvers.jl:150

julia> ENV["GUROBI_HOME"]
"C:\gurobi751\win64"

My Gurobi version is 0.3.3 and in the following line is stated in the /deps/build.jl file:

aliases = ["gurobi75","gurobi70","gurobi65","gurobi60","gurobi56","gurobi55"]

Do you have any suggestions/ tips?

Thanks!
Steffie

Large coefficients

As raised here, when setting the objective Gurobi silently rounds numbers greater than 1e100 down to 1e100.

using JuMP, Gurobi
m = Model(solver=GurobiSolver())
@variable(m, x >= 1)
@objective(m, Min, 1.1e100 * x)
solve(m) # :Optimal
getobjectivevalue(m) # 1.0e100 not 1.1e100

This also happens when setting other values such as the RHS. This is probably because Gurobi just rounds inputs to GRB_INFINITY (1e100).

Things also get weird around variable bounds. It ignores variable bounds larger than or equal to 1e20 (when +ve and upper, or -ve and lower)

using JuMP, Gurobi
m = Model(solver=GurobiSolver())
@variable(m, x <= 1e20)
@objective(m, Min, x)
solve(m) # unbounded
# ... or ...
# @variable(m, x >= -1e20)
# @objective(m, Max, x)

But when -ve and upper or +ve and lower, it allows up to 1e30

using JuMP, Gurobi
m = Model(solver=GurobiSolver())
@variable(m, x >= 1e30)
@objective(m, Min, x)
solve(m) # infeasible (default upper bound is 1e30)
# ... or
@variable(m, x <= -1e30)
@objective(m, Max x)

These "features" are also present in the Python interface.

Not really sure what we should do about it.

Finalizer for Env

Eli complained today about memory becoming saturated with a (small) model in a tight loop. I thought this was fixed when we changed the behavior in CPLEX.jl, but it doesn't look like it.

cc @mlubin @IainNZ

Confirmed upstream bug: get/set of objective coefficients

See https://groups.google.com/forum/#!topic/gurobi/R9SuKdb8YHc for the discussion.

Files demonstrating this (in both Julia and Python) are here
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3

Briefly:

After solving some LP, we add a new constraint
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-main-jl-L25-L26

During the subsequent resolve (https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-main-jl-L30), Gurobi reformulates the model

The LP (and MPS) file of the model at this stage leaks this reformulation (minor bug).
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-3_julia-jl-L1-L16

However, this leak does not occur through the other API's. Therefore, when we get the objective coefficients, we query the original coefficients.
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-main-jl-L34

When we set the objective coefficients (which on resolve, JuMP always does using the original JuMP model coefficients https://github.com/JuliaOpt/JuMP.jl/blob/master/src/solvers.jl#L356 ), we trigger a bug, overriding the reformulated coefficients with this original coefficients.
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-main-jl-L35

In the next solve, Gurobi "undoes" the formulation, but doesn't account for us resetting the correct (but incorrect for that formulation) coefficients (major bug).

This creates the unboundedness.
https://gist.github.com/odow/5255c34daef85a752da76b3836f20be3#file-julia-log-L39

This is pretty worrying for any model solved with JuMP and Gurobi as JuMP always performs this supposed no-op of getting and setting the objective coefficients. If Gurobi has ever reformulated a model in a way that is not unbounded, there would be no way of knowing (short of manually recalculating the objective) that the objective coefficients were switched, leading to an incorrect solution.

@mlubin

Gurobi.free_env segfaults with low probability

Running the following:

using Gurobi, JuMP

while true
    env = Gurobi.Env()
    m = Model(solver=GurobiSolver(env, OutputFlag=0))
    @variable m x
    @objective m Min x^2
    solve(m)
    Gurobi.free_env(env)
end

causes Julia to segfault after a few seconds with:

*** Error in `julia': corrupted double-linked list: 0x0000000003735d20 ***

gdb shows the following:

*** Error in `/usr/local/bin/julia': corrupted double-linked list: 0x0000000002f025f0 ***

Program received signal SIGABRT, Aborted.
0x00007ffff6d24c37 in __GI_raise (sig=sig@entry=6) at ../nptl/sysdeps/unix/sysv/linux/raise.c:56
56      ../nptl/sysdeps/unix/sysv/linux/raise.c: No such file or directory.
(gdb) bt
#0  0x00007ffff6d24c37 in __GI_raise (sig=sig@entry=6) at ../nptl/sysdeps/unix/sysv/linux/raise.c:56
#1  0x00007ffff6d28028 in __GI_abort () at abort.c:89
#2  0x00007ffff6d612a4 in __libc_message (do_abort=do_abort@entry=1, 
    fmt=fmt@entry=0x7ffff6e6f6b0 "*** Error in `%s': %s: 0x%s ***\n") at ../sysdeps/posix/libc_fatal.c:175
#3  0x00007ffff6d6cb02 in malloc_printerr (ptr=0x2f025f0, str=0x7ffff6e6b7e4 "corrupted double-linked list", 
    action=1) at malloc.c:4996
#4  malloc_consolidate (av=av@entry=0x7ffff70ac760 <main_arena>) at malloc.c:4157
#5  0x00007ffff6d6d45d in _int_free (av=0x7ffff70ac760 <main_arena>, p=<optimized out>, have_lock=0)
    at malloc.c:4057
#6  0x00007fffcda0c1be in PRIVATE00000000000620d1 ()
   from /home/rdeits/Applications/gurobi750/linux64/lib/libgurobi75.so
#7  0x00007fffcda0addc in GRBfreemodel () from /home/rdeits/Applications/gurobi750/linux64/lib/libgurobi75.so

I'm running the following Julia version:

julia> versioninfo()
Julia Version 0.6.0
Commit 9036443 (2017-06-19 13:05 UTC)
Platform Info:
  OS: Linux (x86_64-pc-linux-gnu)
  CPU: Intel(R) Core(TM) i7-3920XM CPU @ 2.90GHz
  WORD_SIZE: 64
  BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Sandybridge)
  LAPACK: libopenblas64_
  LIBM: libopenlibm
  LLVM: libLLVM-3.9.1 (ORCJIT, ivybridge)

and the following Gurobi version:

julia> Gurobi.version
v"7.5.0"

julia> Pkg.installed("Gurobi")
v"0.3.3+"

I'm not entirely sure that this is a Gurobi.jl issue, but I have noticed that just constructing and freeing environments seems to work fine. That is, the following does not crash:

while true
  env = Gurobi.Env()
  Gurobi.free_env(env)
end

getobjgap not implemented

Hello

I could not get the gap out of a Gurobi model, I don't see the function implemented in the code.

regards

Interface completion

We already support a lot of the interface, so lets push for 100%. This was taken from the 5.6 Reference Manual: http://www.gurobi.com/documentation/5.6/reference-manual/refman

Environment Creation and Destruction

• GRBloadenv (as the constructor for Env - consider adding a gurobi_env() function which does same for consistency with style of rest of API, esp. model constructor. Should probably support logfilename as optional argument)
• GRBloadclientenv (compute server-related - ignore)
• GRBfreeenv
• GRBgetconcurrentenv
• GRBdiscardconcurrentenvs

Model Creation and Modification

• GRBloadmodel
• GRBnewmodel
• GRBcopymodel
• GRBaddconstr
• GRBaddconstrs
• GRBaddqconstr
• GRBaddqpterms
• GRBaddrangeconstr
• GRBaddrangeconstrs
• GRBaddsos
• GRBaddvar
• GRBaddvars
• GRBchgcoeffs
• GRBdelconstrs
• GRBdelq
• GRBdelqconstrs
• GRBdelsos
• GRBdelvars
• GRBupdatemodel
• GRBfreemodel

Model Solution

• GRBoptimize
• GRBcomputeIIS
• GRBfeasrelax
• GRBfixedmodel
• GRBresetmodel
• GRBsync

Model Queries

• GRBgetcoeff
• GRBgetconstrbyname
• GRBgetconstrs
• GRBgetenv
• GRBgetq
• GRBgetqconstr
• GRBgetsos
• GRBgetvarbyname
• GRBgetvars

Input/Output

• GRBreadmodel
• GRBread
• GRBwrite

Attribute Management

• GRBgetattrinfo
• GRBgetintattr
• GRBsetintattr
• GRBgetintattrelement
• GRBsetintattrelement
• GRBgetintattrarray
• GRBsetintattrarray
• GRBgetintattrlist
• GRBsetintattrlist
• GRBgetdblattr
• GRBsetdblattr
• GRBgetdblattrelement
• GRBsetdblattrelement
• GRBgetdblattrarray
• GRBsetdblattrarray
• GRBgetdblattrlist
• GRBsetdblattrlist
• GRBgetcharattrelement
• GRBsetcharattrelement
• GRBgetcharattrarray
• GRBsetcharattrarray
• GRBgetcharattrlist
• GRBsetcharattrlist
• GRBgetstrattr
• GRBsetstrattr
• GRBgetstrattrelement
• GRBsetstrattrelement
• GRBgetstrattrarray
• GRBsetstrattrarray
• GRBgetstrattrlist
• GRBsetstrattrlist

Parameter Management and Tuning

• GRBtunemodel
• GRBgettuneresult
• GRBgetdblparam
• GRBgetintparam
• GRBgetstrparam
• GRBsetdblparam
• GRBsetintparam
• GRBsetstrparam
• GRBgetdblparaminfo
• GRBgetintparaminfo
• GRBgetstrparaminfo
• GRBreadparams
• GRBwriteparams

Monitoring Progress - Logging and Callbacks

• GRBmsg
• GRBsetcallbackfunc
• GRBgetcallbackfunc
• GRBcbget
• GRBversion

Modifying Solver Behavior - Callbacks

• GRBcbcut
• GRBcblazy
• GRBcbsolution
• GRBterminate

Error Handling

• GRBgeterrormsg

Advanced simplex routines

• GRBFSolve
• GRBBSolve
• GRBinvColj
• GRBinvRowi
• GRBgetBasisHead

set_intattr! not working

Suppose I create a Gurobi.Model, called m. Then I do this:

Gurobi.set_intattr!(model, "NumObj", 10)
Gurobi.get_intattr(model, "NumObj")

Interestingly, the last line returns 1, instead of 10. Why is NumObj not being modified here?

Gurobi license error

I'm getting the error below when I try to call Gurobi through JuMP. I am able to call Gurobi from Python. Do I need to set GUROBI_HOME environment variable? My Gurobi license is set up to run Gurobi on a remote server.

Capacity available on '10.60.129.38' - connecting...
Established 256-bit AES encrypted connection
ERROR: LoadError: Invalid Gurobi license
Stacktrace:
[1] Gurobi.Env() at /Users/a598124/.julia/v0.6/Gurobi/src/grb_env.jl:13
[2] include_from_node1(::String) at ./loading.jl:576
[3] include(::String) at ./sysimg.jl:14
[4] process_options(::Base.JLOptions) at ./client.jl:305
[5] _start() at ./client.jl:371
while loading /Users/a598124/juliaCode/boxPacking1/monroe.jl, in expression starting on line 3

Gurobi.jl v0.2.8 "unable to locate Gurobi installation"

Hello,
I had Gurobi.jl installed and it worked fine until I did a Package update yesterday.
Now, with Gurobi.jl v0.2.8 I get the error "unable to locate Gurobi installation" even though GUROBI_HOME is set to the right path in terminal (If I type 'gurobi.sh' in terminal it works just fine). I use julia v0.5.0 on Ubuntu 16.04.

Support hierarchical (or lexicographic) multi-objective linear programming?

Hierarchical linear programming is when you have more than one objective, and you optimize them hierarchically. For example, if z1 is the optimal result from the first objective, you then optimize the second objective, but adding the contstrain that the first objective function is fixed at z1, and so on.

Gurobi has an interface for this, as I gather from the manual. It would be nice if this were ported to Gurobi.jl.

Note that simply doing the two optimizations by hand seems to have numerical issues in my experience. I have found that frequently the secondary optimization is seen as infeasible.

error compiling getlibversion

On Windows_7_x64 installed julia-0.6.2-win64.exe

File gurobi75.dll in D:\Julia\Solvers\bin

julia> ENV["GUROBI_HOME"]
"D:\\Julia\\Solvers"

julia> Pkg.add("Gurobi")
INFO: Installing Gurobi v0.3.3
INFO: Building Gurobi
INFO: Package database updated

julia> include("C:\\Users\\User\\.julia\\v0.6\\Gurobi\\test\\mip_01.jl")
INFO: Precompiling module Gurobi.
ERROR: LoadError: LoadError: error compiling getlibversion: could not load libra
ry "D:JuliaSolveringurobi75.dll"
The specified module could not be found.

Stacktrace:
 [1] include_from_node1(::String) at .\loading.jl:576
 [2] include(::String) at .\sysimg.jl:14
 [3] include_from_node1(::String) at .\loading.jl:576
 [4] include(::String) at .\sysimg.jl:14
 [5] anonymous at .\<missing>:2
while loading C:\Users\User\.julia\v0.6\Gurobi\src\grb_common.jl, in expression
starting on line 72
while loading C:\Users\User\.julia\v0.6\Gurobi\src\Gurobi.jl, in expression star
ting on line 66
ERROR: LoadError: Failed to precompile Gurobi to C:\Users\User\.julia\lib\v0.6\G
urobi.ji.
Stacktrace:
 [1] compilecache(::String) at .\loading.jl:710
 [2] _require(::Symbol) at .\loading.jl:497
 [3] require(::Symbol) at .\loading.jl:405
 [4] include_from_node1(::String) at .\loading.jl:576
 [5] include(::String) at .\sysimg.jl:14
while loading C:\Users\User\.julia\v0.6\Gurobi\test\mip_01.jl, in expression sta
rting on line 13

Support attributes

It'd be good if attributes were supported so objectives, bounds, etc. could be updated

C: GRBsetdblattrelement(model, "Obj", j, cost[j]);
Julia: setAttrElement!(model, "Obj", j, cost[j])

EDIT: I see these are actually there, but not exported - is something broken with them?

Parallel Solves

I have a JuMP (mixed-integer) model where I'm trying to determine the upper and lower bounds on many variables. Each individual solve is very quick, but since I have many variables (~1,000), the overall solve time is slow (~5s).

One thing that I observed is that julia often seems to be using only one core at a time, and I was hoping that parallelization might be able to reduce solve times significantly. However, I'm running into an issue that seems to have to do with there being only a single Gurobi environment created.

Here's an example of a snippet of code that doesn't work. (map runs fine, but pmap does not).

addprocs(2)

using JuMP
using Gurobi

@everywhere begin
env = Gurobi.Env()
m = JuMP.Model(solver = Gurobi.GurobiSolver(env, OutputFlag=0))

@JuMP.variable(m, 0 <= x[i=1:100] <= i)

function upperbound_mip(x)
    @JuMP.objective(x.m, Max, x)
    JuMP.solve(x.m)
    return JuMP.getobjectivevalue(x.m)
end
end

@time map(upperbound_mip, x)
@time pmap(upperbound_mip, x)

Output

Academic license - for non-commercial use only
	From worker 3:	Academic license - for non-commercial use only
	From worker 2:	Academic license - for non-commercial use only 
 2.317813 seconds (1.72 M allocations: 90.407 MiB, 1.04% gc time)
ERROR: LoadError: On worker 2:
AssertionError: env.ptr_env != C_NULL
get_error_msg at /home/vtjeng/.julia/v0.6/Gurobi/src/grb_env.jl:38
Type at /home/vtjeng/.julia/v0.6/Gurobi/src/grb_env.jl:50 [inlined]
get_intattr at /home/vtjeng/.julia/v0.6/Gurobi/src/grb_attrs.jl:16
setvarLB! at /home/vtjeng/.julia/v0.6/Gurobi/src/GurobiSolverInterface.jl:187
#build#119 at /home/vtjeng/.julia/v0.6/JuMP/src/solvers.jl:338
#build at ./<missing>:0
#solve#116 at /home/vtjeng/.julia/v0.6/JuMP/src/solvers.jl:168
upperbound_mip at /home/vtjeng/Dropbox/Documents/MIT/UROP/adversarial_examples/pset/6_using_MIPVerify/debug/feature-parallel-solves.jl:14
#106 at ./distributed/process_messages.jl:268 [inlined]
run_work_thunk at ./distributed/process_messages.jl:56
macro expansion at ./distributed/process_messages.jl:268 [inlined]
#105 at ./event.jl:73
Stacktrace:
 [1] #571 at ./asyncmap.jl:178 [inlined]
 [2] foreach(::Base.##571#573, ::Array{Any,1}) at ./abstractarray.jl:1733
 [3] maptwice(::Function, ::Channel{Any}, ::Array{Any,1}, ::Array{JuMP.Variable,1}, ::Vararg{Array{JuMP.Variable,1},N} where N) at ./asyncmap.jl:178
 [4] wrap_n_exec_twice(::Channel{Any}, ::Array{Any,1}, ::Base.Distributed.##204#207{WorkerPool}, ::Function, ::Array{JuMP.Variable,1}, ::Vararg{Array{JuMP.Variable,1},N} where N) at ./asyncmap.jl:154
 [5] #async_usemap#556(::Function, ::Void, ::Function, ::Base.Distributed.##188#190, ::Array{JuMP.Variable,1}, ::Vararg{Array{JuMP.Variable,1},N} where N) at ./asyncmap.jl:103
 [6] (::Base.#kw##async_usemap)(::Array{Any,1}, ::Base.#async_usemap, ::Function, ::Array{JuMP.Variable,1}, ::Vararg{Array{JuMP.Variable,1},N} where N) at ./<missing>:0
 [7] (::Base.#kw##asyncmap)(::Array{Any,1}, ::Base.#asyncmap, ::Function, ::Array{JuMP.Variable,1}) at ./<missing>:0
 [8] #pmap#203(::Bool, ::Int64, ::Void, ::Array{Any,1}, ::Void, ::Function, ::WorkerPool, ::Function, ::Array{JuMP.Variable,1}) at ./distributed/pmap.jl:126
 [9] pmap(::WorkerPool, ::Function, ::Array{JuMP.Variable,1}) at ./distributed/pmap.jl:101
 [10] #pmap#213(::Array{Any,1}, ::Function, ::Function, ::Array{JuMP.Variable,1}) at ./distributed/pmap.jl:156
 [11] pmap(::Function, ::Array{JuMP.Variable,1}) at ./distributed/pmap.jl:156
 [12] include_from_node1(::String) at ./loading.jl:576
 [13] include(::String) at ./sysimg.jl:14
 [14] process_options(::Base.JLOptions) at ./client.jl:305
 [15] _start() at ./client.jl:371

One thing I've thought about trying to do is to generate one environment per worker thread, but 1) I don't know whether that would help and 2) I don't know how to do that.

Move the ownership to JuliaOpt

Whereas I created this for a project, I don't see I may be able to maintain it for a long term. Moving this package to JuliaOpt may help to keep the development active.

So I am proposing moving the ownership over to JuliaOpt. After the move, I will continue to contribute to it.

cc: @IainNZ @mlubin

getsolution() returns infeasible solution for an unbounded problem

On this problem,

Min y
s.t. x >= 1
loadproblem!(m, [1. 0.], [-Inf, -Inf], [Inf, Inf], [0., 1.], [1.], [Inf], :Min)

calling optimize! returns :Unbounded and then getsolution gives [6.93747e-310,0.0] which is not feasible since x = 6.93747e-310 < 1 (I am using Gurobi 6.51).

However, it seems that in Gurobi getsolution gives a feasible solution even for unbounded problem since for the following problem

Max x
s.t. x >= 1
x unbounded
y <= -1
loadproblem!(m, [1. 0.], [-Inf, -Inf], [Inf, -1], [1., 0.], [1], [Inf], :Max)

optimize! returns :Unbounded and then getsolution returns a feasible solution.

See JuliaOpt/MathProgBase.jl#144

finish linprogsolver implementation

We finally have some unit tests for LinprogSolver.

using Gurobi
include(joinpath(Pkg.dir("MathProgBase"),"test","linproginterface.jl"))

m = Gurobi.model()
linprogsolvertest(m)

ERROR: test error during :((getvarLB(m)==[0.0,0.0]))
Not Implemented
 in anonymous at test.jl:63
 in do_test at test.jl:36
 in linprogsolvertest at /home/mlubin/.julia/MathProgBase/test/linproginterface.jl:13

Set constructor breaks on Julia master

On commit JuliaLang/julia@4e84913

julia> using Gurobi
ERROR: no method Set{ASCIIString}(ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString, ASCIIString)
you may have intended to import Base.Set
 in reload_path at loading.jl:144
 in _require at loading.jl:59
 in require at loading.jl:43
while loading /Users/huchette/.julia/v0.3/Gurobi/src/grb_params.jl, in expression starting on line 9
while loading /Users/huchette/.julia/v0.3/Gurobi/src/Gurobi.jl, in expression starting on line 63

Seems sets should be specified Set(["a", "b"]) now; this will probably break on 0.2 though

Omission in Documentation?

I'm new to using Gurobi in Julia, so I was following your README, looking at the examples. In particular, I was looking at Example 1.4. I could run the code and solve the optimization problem, but I noticed that any parameters I attempted to manipulate through a combination of

 env = Gurobi.Env()

and

 setparam!(env, name, v) 

had no effect on the results.

After more time than I care to admit, I realized that the problem was the following line in Example 1.4:

m = Model(solver=GurobiSolver())

As soon as I updated this to read

m = Model(solver=GurobiSolver(env))

My parameter manipulations had the expected effect.

For the seasoned Gurobi users out there, it is perhaps obvious that we somehow need to inform Gurobi of the changes made to the environment. However, this was not obvious to a noob like me. You might consider updating the troublesome line in Example 1.4 to spare future noobs the same confusion.

Compatibility w. Gurobi 6?

Hey all,

One of my colleagues (Ramandeep) said he recently tried to pull down JuMP and Gurobi and get it working and it would not work with Gurobi 6, but does work with Gurobi 5.6...

Granted, this is not exactly a reproducible use case, and it may have been something else entirely, but I thought I'd flag it with all of you just in case.

Vishal

Document solve status codes

jump-dev/JuMP.jl#141

GurobiSolver ignores constant term in objective

It appears that GurobiSolver ignores any constant terms in the JuMP model's cost function. For example:

using JuMP, Gurobi

model = Model(solver=GurobiSolver(OutputFlag=1))
@variable model x
@objective model Min x^2 - 1
solve(model)

The gurobi output shows:

Optimize a model with 0 rows, 1 columns and 0 nonzeros
Model has 1 quadratic objective term
Coefficient statistics:
  Matrix range     [0e+00, 0e+00]
  Objective range  [0e+00, 0e+00]
  QObjective range [2e+00, 2e+00]
  Bounds range     [0e+00, 0e+00]
  RHS range        [0e+00, 0e+00]
Presolve removed 0 rows and 1 columns
Presolve time: 0.00s
Presolve: All rows and columns removed

Barrier solved model in 0 iterations and 0.00 seconds
Optimal objective 0.00000000e+00

but the optimal objective value is actually -1, as confirmed by JuMP:

getvalue(getobjective(model))
# -1.0

Of course, for most optimization problems this is fine. Any constant term in the objective doesn't affect the minimizer, and JuMP still reports the correct final objective with getvalue().

However, there is one case in which this absolutely does matter: mixed-integer programming. When solving an MIP, Gurobi checks optimality by measuring (among other things), the relative gap between the best incumbent and the best bound. Since this gap is relative to the actual cost value, adding an arbitrary constant offset (or failing to add one) will affect whether the MIP gap is considered small enough.

This is causing some trouble for me, since I see very different solve times depending on how the particular initial state of my system affects the (eliminated) constant term in the cost.

Is there any way to turn this on in Gurobi.jl? I'd be happy to do the work myself, but I'd appreciate some pointers on where to look, since I haven't used the internal Gurobi interface at all.

I am not able to optimize models using gurobi. I have the license version 7.0.2 and Julia 0.5.1/ can you help me out. I have captured error message.

ERROR: `add_cvars!` has no method matching add_cvars!(::Model, ::Array{Float64,2}, ::Array{Float64,1}, ::Array{Float64,1})

I'm trying to use Convex.jl with Gurobi

using Convex, Gurobi
x = Variable()
y = Variable(Positive())
p = minimize(x+y,x==1)
solve!(p, GurobiSolver())

and I get

ERROR: `add_cvars!` has no method matching add_cvars!(::Model, ::Array{Float64,2}, ::Array{Float64,1}, ::Array{Float64,1})
 in loadproblem! at /Users/karanveer/.julia/v0.3/Gurobi/src/GurobiSolverInterface.jl:35
 in loadconicproblem! at /Users/karanveer/.julia/v0.3/MathProgBase/src/SolverInterface/conic.jl:105
 in solve! at /Users/karanveer/.julia/v0.3/Convex/src/solution.jl:31
 in solve! at /Users/karanveer/.julia/v0.3/Convex/src/solution.jl:66

I can change line 35 of GurobiSolverInterface.jl to:
add_cvars!(m.inner, float(vec(obj)), float(collb), float(colub))
and the relevant Convex.jl tests all pass, but is that the best place for that change to be made, or should something differently be done in MPB?

What is the meaning of "rowinds", "colinds", "coeffs" in Example 2.2?

Hi, I am trying to solve a MIQP problem and feel confused about some of your arguments... Could you please tell me what is the meaning of "rowinds", "colinds", "coeffs" in Example 2.2? Thank you very much in advance. :)

# add quadratic terms: x^2, x * y, y^2
# add_qpterms!(model, rowinds, colinds, coeffs)
add_qpterms!(model, [1, 1, 2], [1, 2, 2], [1., 1., 1.])

Library not found on OS X

The gurobi library on OS X is a .so file instead of a .dylib file, so BinDeps can't find it.

callbacks broken on win32

Gurobi expects the callbacks to follow the stdcall convention.