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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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using JSON2
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import Base: dump
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get_instance_features(instance) = [0.]
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get_variable_features(instance, var, index) = [0.]
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find_violated_lazy_constraints(instance, model) = []
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build_lazy_constraint(instance, model, v) = nothing
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dump(instance::PyCall.PyObject, filename) = @pycall instance.dump(filename)
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load!(instance::PyCall.PyObject, filename) = @pycall instance.load(filename)
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macro Instance(klass)
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quote
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@pydef mutable struct Wrapper <: Instance
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function __init__(self, args...; kwargs...)
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self.data = $(esc(klass))(args...; kwargs...)
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end
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function dump(self, filename)
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prev_data = self.data
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self.data = JSON2.write(prev_data)
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Instance.dump(self, filename)
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self.data = prev_data
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end
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function load(self, filename)
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Instance.load(self, filename)
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self.data = JSON2.read(self.data, $(esc(klass)))
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end
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to_model(self) =
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$(esc(:to_model))(self.data)
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get_instance_features(self) =
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get_instance_features(self.data)
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get_variable_features(self, var, index) =
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get_variable_features(self.data, var, index)
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function find_violated_lazy_constraints(self, model)
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find_violated_lazy_constraints(self.data, model)
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end
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function build_lazy_constraint(self, model, v)
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build_lazy_constraint(self.data, model, v)
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end
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end
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end
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end
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export get_instance_features,
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get_variable_features,
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find_violated_lazy_constraints,
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build_lazy_constraint,
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dump,
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load!,
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@Instance
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@ -1,32 +0,0 @@
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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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using PyCall
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@pydef mutable struct KnapsackInstance <: Instance
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function __init__(self, weights, prices, capacity)
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self.weights = weights
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self.prices = prices
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self.capacity = capacity
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end
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function to_model(self)
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model = Model()
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n = length(self.weights)
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@variable(model, x[1:n], Bin)
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@objective(model, Max, sum(x[i] * self.prices[i] for i in 1:n))
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@constraint(model, sum(x[i] * self.weights[i] for i in 1:n) <= self.capacity)
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return model
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end
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function get_instance_features(self)
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return [0.]
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end
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function get_variable_features(self, var, index)
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return [0.]
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end
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end
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export KnapsackInstance
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@ -0,0 +1,28 @@
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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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struct LearningSolver
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py::PyCall.PyObject
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end
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function LearningSolver(;
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optimizer,
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kwargs...,
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)::LearningSolver
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py = @pycall miplearn.LearningSolver(;
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kwargs...,
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solver=JuMPSolver(optimizer=optimizer))
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return LearningSolver(py)
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end
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solve!(solver::LearningSolver, instance; kwargs...) =
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@pycall solver.py.solve(instance; kwargs...)
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fit!(solver::LearningSolver, instances; kwargs...) =
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@pycall solver.py.fit(instances; kwargs...)
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add!(solver::LearningSolver, component; kwargs...) =
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@pycall solver.py.add(component; kwargs...)
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export LearningSolver
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@ -0,0 +1,34 @@
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# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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import MIPLearn: get_instance_features,
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get_variable_features
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find_violated_lazy_constraints
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using JuMP
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struct KnapsackData
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weights
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prices
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capacity
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end
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function to_model(data::KnapsackData)
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model = Model()
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n = length(data.weights)
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@variable(model, x[1:n], Bin)
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@objective(model, Max, sum(x[i] * data.prices[i] for i in 1:n))
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@constraint(model, sum(x[i] * data.weights[i] for i in 1:n) <= data.capacity)
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return model
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end
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function get_instance_features(data::KnapsackData)
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return [0.]
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end
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function get_variable_features(data::KnapsackData, var, index)
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return [0.]
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end
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KnapsackInstance = @Instance(KnapsackData)
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