Add reset! for solver

src/solver.jl

@@ -5,6 +5,15 @@ abstract type AbstractSolver end
 
 abstract type AbstractOptimizationSolver <: AbstractSolver end
 
+"""
+    reset!(solver::AbstractOptimizationSolver, model::AbstractNLPModel)
+
+Use in the context of restarting or reusing the `solver` structure.
+Reset the internal fields of `solver` for the `model` before calling `solve!` on the same structure.
+`model` must have the same number of variables, bounds and constraints as that used to instantiate `solver`.
+"""
+function NLPModels.reset!(::AbstractOptimizationSolver, ::AbstractNLPModel) end
+
 """
     solve!(solver, model; kwargs...)
     solve!(solver, model, stats; kwargs...)

test/runtests.jl

@@ -12,3 +12,4 @@ include("dummy_solver.jl")
 include("test_logging.jl")
 include("test_stats.jl")
 include("test_callback.jl")
+include("test_restart.jl")

test/test_restart.jl

@@ -0,0 +1,17 @@
+@testset "test restart" begin
+  nlp = ADNLPModel(x -> dot(x, x) / 2, ones(2), x -> [sum(x .^ 3) - 1], [0.0], [0.0])
+  solver = DummySolver(nlp)
+  stats = GenericExecutionStats(nlp)
+  solve!(solver, nlp, stats, verbose = false)
+  @test stats.status == :first_order
+  # Try with a new intial guess
+  nlp.meta.x0 .= 0.2
+  reset!(solver, nlp)
+  solve!(solver, nlp, stats, verbose = false)
+  @test stats.status == :first_order
+  # Try with a new problem of the same size
+  nlp = ADNLPModel(x -> dot(x, x) / 2, ones(2), x -> [sum(x .^ 3)], [0.0], [0.0])
+  reset!(solver, nlp)
+  solve!(solver, nlp, stats, verbose = false)
+  @test stats.status == :first_order
+end