DNM: Fix various Threading() bugs

docs/src/examples/belief.jl

@@ -58,8 +58,9 @@ function inventory_management_problem()
         iteration_limit = 100,
         cut_type = SDDP.SINGLE_CUT,
         log_frequency = 10,
+        parallel_scheme = SDDP.Serial(),
     )
-    results = SDDP.simulate(model, 500)
+    results = SDDP.simulate(model, 500; parallel_scheme = SDDP.Serial())
     objectives =
         [sum(s[:stage_objective] for s in simulation) for simulation in results]
     sample_mean = round(Statistics.mean(objectives); digits = 2)

docs/src/examples/infinite_horizon_hydro_thermal.jl

@@ -54,6 +54,7 @@ function infinite_hydro_thermal(; cut_type)
         cut_type = cut_type,
         log_frequency = 100,
         sampling_scheme = SDDP.InSampleMonteCarlo(; terminate_on_cycle = true),
+        parallel_scheme = SDDP.Serial(),
         cycle_discretization_delta = 0.1,
     )
     @test SDDP.calculate_bound(model) ≈ 119.167 atol = 0.1

docs/src/examples/the_farmers_problem.jl

@@ -245,10 +245,10 @@ end
 # ## Training a policy
 
 # Now that we've built a model, we need to train it using [`SDDP.train`](@ref).
-# The keyword `iteration_limit` stops the training after 20 iterations. See
+# The keyword `iteration_limit` stops the training after 40 iterations. See
 # [Choose a stopping rule](@ref) for other ways to stop the training.
 
-SDDP.train(model; iteration_limit = 20)
+SDDP.train(model; iteration_limit = 40)
 
 # ## Checking the policy