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MIPLearn
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Improve JuMPSolver performance

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pull/3/head
Alinson S. Xavier 5 years ago
parent 0cf1939325
commit 5480b196f5
3 changed files with 130 additions and 57 deletions
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13
src/julia/Manifest.toml
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@ -164,6 +164,7 @@ uuid = "aa1ae85d-cabe-5617-a682-6adf51b2e16a"
version = "0.7.13"
[[LibGit2]]
deps = ["Printf"]
uuid = "76f85450-5226-5b5a-8eaa-529ad045b433"
[[Libdl]]
@ -212,9 +213,9 @@ version = "1.0.1"
[[MbedTLS_jll]]
deps = ["Libdl", "Pkg"]
git-tree-sha1 = "066a4467008745eed36dad973ceb66405785a621"
git-tree-sha1 = "c83f5a1d038f034ad0549f9ee4d5fac3fb429e33"
uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"
version = "2.16.0+1"
version = "2.16.0+2"
[[Mmap]]
uuid = "a63ad114-7e13-5084-954f-fe012c677804"
@ -249,7 +250,7 @@ uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
version = "1.0.1"
[[Pkg]]
deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "Test", "UUIDs"]
deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "UUIDs"]
uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
[[Printf]]
@ -309,6 +310,12 @@ uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[[TimerOutputs]]
deps = ["Printf"]
git-tree-sha1 = "0cc8db57cb537191b02948d4fabdc09eb7f31f98"
uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
version = "0.5.5"
[[TinyBnB]]
deps = ["CPLEXW", "Printf", "Random", "Revise", "Test"]
git-tree-sha1 = "921ad42ac9dd4d44e42941eb63c59bcb50f30b6f"

5
src/julia/Project.toml
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@ -12,4 +12,9 @@ MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
TinyBnB = "1b2a1171-e557-4eeb-a4d6-6c23d7e94fcd"
[compat]
CPLEX = "0.6"
JuMP = "0.21"

169
src/julia/src/jump_solver.jl
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@ -3,17 +3,39 @@
# Released under the modified BSD license. See COPYING.md for more details.
using JuMP
using CPLEX
using MathOptInterface
const MOI = MathOptInterface
using TimerOutputs
mutable struct JuMPSolverData
basename_idx_to_var
var_to_basename_idx
optimizer
instance
model
bin_vars
solution
end
function varname_split(varname::String)
m = match(r"([^[]*)\[(.*)\]", varname)
if m == nothing
return varname, ""
end
return m.captures[1], m.captures[2]
end
@pydef mutable struct JuMPSolver <: InternalSolver
function __init__(self; optimizer=CPLEX.Optimizer)
self.optimizer = optimizer
function __init__(self; optimizer=nothing)
self.data = JuMPSolverData(nothing, # basename_idx_to_var
nothing, # var_to_basename_idx
optimizer,
nothing, # instance
nothing, # model
nothing, # bin_vars
nothing, # solution
)
end
function add_constraint(self, constraint)
@ -21,10 +43,11 @@ end
end
function set_warm_start(self, solution)
basename_idx_to_var = self.data.basename_idx_to_var
for (basename, subsolution) in solution
for (idx, value) in subsolution
value != nothing || continue
var = self.basename_idx_to_var[basename, idx]
var = basename_idx_to_var[basename, idx]
JuMP.set_start_value(var, value)
end
end
@ -35,88 +58,126 @@ end
end
function fix(self, solution)
for (basename, subsolution) in solution
for (idx, value) in subsolution
value != nothing || continue
var = self.basename_idx_to_var[basename, idx]
JuMP.fix(var, value, force=true)
@timeit "fix" begin
basename_idx_to_var = self.data.basename_idx_to_var
for (basename, subsolution) in solution
for (idx, value) in subsolution
value != nothing || continue
var = basename_idx_to_var[basename, idx]
JuMP.fix(var, value, force=true)
end
end
end
end
function set_instance(self, instance, model)
self.instance = instance
self.model = model
self.var_to_basename_idx = Dict(var => varname_split(JuMP.name(var))
for var in JuMP.all_variables(self.model))
self.basename_idx_to_var = Dict(varname_split(JuMP.name(var)) => var
for var in JuMP.all_variables(self.model))
self.bin_vars = [var
for var in JuMP.all_variables(self.model)
if JuMP.is_binary(var)]
JuMP.set_optimizer(self.model, self.optimizer)
@timeit "set_instance" begin
self.data.instance = instance
self.data.model = model
self.data.var_to_basename_idx = Dict(var => varname_split(JuMP.name(var))
for var in JuMP.all_variables(model))
self.data.basename_idx_to_var = Dict(varname_split(JuMP.name(var)) => var
for var in JuMP.all_variables(model))
self.data.bin_vars = [var
for var in JuMP.all_variables(model)
if JuMP.is_binary(var)]
if self.data.optimizer != nothing
JuMP.set_optimizer(model, self.data.optimizer)
end
end
end
function solve(self; tee=false)
JuMP.optimize!(self.model)
self._update_solution()
primal_bound = JuMP.objective_value(self.model)
dual_bound = JuMP.objective_bound(self.model)
if JuMP.objective_sense(self.model) == MOI.MIN_SENSE
sense = "min"
lower_bound = dual_bound
upper_bound = primal_bound
else
sense = "max"
lower_bound = primal_bound
upper_bound = dual_bound
@timeit "solve" begin
instance, model = self.data.instance, self.data.model
wallclock_time = 0
found_violations = []
while true
@timeit "optimize!" begin
JuMP.optimize!(model)
end
wallclock_time += JuMP.solve_time(model)
@timeit "find_violations" begin
violations = instance.find_violations(model)
end
@info "$(length(violations)) violations found"
if length(violations) == 0
break
end
append!(found_violations, violations)
for v in violations
instance.build_lazy_constraint(self.data.model, v)
end
end
@timeit "update solution" begin
self._update_solution()
self.data.instance.found_violations = found_violations
end
primal_bound = JuMP.objective_value(model)
dual_bound = JuMP.objective_bound(model)
if JuMP.objective_sense(model) == MOI.MIN_SENSE
sense = "min"
lower_bound = dual_bound
upper_bound = primal_bound
else
sense = "max"
lower_bound = primal_bound
upper_bound = dual_bound
end
end
@show primal_bound, dual_bound
return Dict("Lower bound" => lower_bound,
"Upper bound" => upper_bound,
"Sense" => sense,
"Wallclock time" => JuMP.solve_time(self.model),
"Wallclock time" => wallclock_time,
"Nodes" => 1,
"Log" => nothing,
"Warm start value" => nothing)
end
function solve_lp(self; tee=false)
for var in self.bin_vars
JuMP.unset_binary(var)
JuMP.set_upper_bound(var, 1.0)
JuMP.set_lower_bound(var, 0.0)
end
JuMP.optimize!(self.model)
obj_value = JuMP.objective_value(self.model)
self._update_solution()
for var in self.bin_vars
JuMP.set_binary(var)
@timeit "solve_lp" begin
model = self.data.model
bin_vars = self.data.bin_vars
@timeit "unset_binary" begin
for var in bin_vars
JuMP.unset_binary(var)
JuMP.set_upper_bound(var, 1.0)
JuMP.set_lower_bound(var, 0.0)
end
end
@timeit "optimize" begin
JuMP.optimize!(model)
end
@timeit "update solution" begin
self._update_solution()
end
obj_value = JuMP.objective_value(model)
@timeit "set_binary" begin
for var in bin_vars
JuMP.set_binary(var)
end
end
end
return Dict("Optimal value" => obj_value)
end
function get_solution(self)
return self.solution
return self.data.solution
end
function _update_solution(self)
var_to_basename_idx, model = self.data.var_to_basename_idx, self.data.model
solution = Dict()
for var in JuMP.all_variables(self.model)
basename, idx = self.var_to_basename_idx[var]
for var in JuMP.all_variables(model)
var in keys(var_to_basename_idx) || continue
basename, idx = var_to_basename_idx[var]
if !haskey(solution, basename)
solution[basename] = Dict()
end
solution[basename][idx] = JuMP.value(var)
end
self.solution = solution
self.data.solution = solution
end
function set_gap_tolerance(self, gap_tolerance)
@ -136,6 +197,6 @@ end
end
function set_time_limit(self, time_limit)
JuMP.set_time_limit_sec(self.model, time_limit)
JuMP.set_time_limit_sec(self.data.model, time_limit)
end
end

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