Add SolverCore.reset!(solver) (#133)

* solver

* JSOSolver

* Update src/NLPModelsIpopt.jl

Co-authored-by: Tangi Migot <[email protected]>

* Update test/runtests.jl

Co-authored-by: Tangi Migot <[email protected]>

* Update test/runtests.jl

Co-authored-by: Tangi Migot <[email protected]>

* Update test/runtests.jl

Co-authored-by: Tangi Migot <[email protected]>

* Update src/NLPModelsIpopt.jl

Co-authored-by: Tangi Migot <[email protected]>

* removed TODO comment and set problem.obj_val to Inf

* Apply suggestions from code review

---------

Co-authored-by: Tangi Migot <[email protected]>

Author: arnavk23

src/NLPModelsIpopt.jl

@@ -93,8 +93,8 @@ function SolverCore.reset!(solver::IpoptSolver, nlp::AbstractNLPModel)
   @assert nlp.meta.nvar == problem.n
   @assert nlp.meta.ncon == problem.m
 
-  problem.obj_val = 0.0
-  problem.status = 0
+  problem.obj_val = Inf
+  problem.status = -1
   problem.x .= nlp.meta.x0
   eval_f, eval_g, eval_grad_f, eval_jac_g, eval_h = set_callbacks(nlp)
   problem.eval_f = eval_f
@@ -108,6 +108,16 @@ function SolverCore.reset!(solver::IpoptSolver, nlp::AbstractNLPModel)
   return problem
 end
 
+function SolverCore.reset!(solver::IpoptSolver)
+  problem = solver.problem
+  
+  problem.obj_val = Inf
+  problem.status = -1  # Use -1 to indicate not solved yet
+  problem.intermediate = nothing
+  
+  return solver
+end
+
 """
     set_callbacks(nlp::AbstractNLPModel)
 

test/runtests.jl

@@ -117,3 +117,24 @@ end
   @test stats.iter >= 0
   @test isapprox(stats.dual_feas, 0.0; atol = 1e-8)
 end
+
+@testset "Test restart with a different initial guess" begin
+  f(x) = (x[1] - 1)^2 + 4 * (x[2] - x[1]^2)^2
+  nlp = ADNLPModel(f, [-1.2; 1.0])
+  stats = GenericExecutionStats(nlp)
+  solver = IpoptSolver(nlp)
+  
+  # Solve the problem first
+  stats = solve!(solver, nlp, stats, print_level = 0)
+  @test stats.status == :first_order
+  @test isapprox(stats.solution, [1.0; 1.0], atol = 1e-6)
+  
+  # Change initial guess and reset solver
+  nlp.meta.x0 .= 2.0
+  reset!(solver)
+  
+  # Solve again with new initial guess
+  stats = solve!(solver, nlp, stats, print_level = 0)
+  @test stats.status == :first_order
+  @test isapprox(stats.solution, [1.0; 1.0], atol = 1e-6)
+end