Merge pull request #69 from leclere/return-control-state-ef

[DEV] return first control with extensive formulation

Author: leclere

examples/dynamic_example.jl

@@ -16,11 +16,11 @@ using StochDynamicProgramming, JuMP, Clp
 const SOLVER = ClpSolver()
 # const SOLVER = CplexSolver(CPX_PARAM_SIMDISPLAY=0)
 
-const N_STAGES = 5
-const N_SCENARIOS = 1
+const N_STAGES = 3
+const N_SCENARIOS = 2
 
 const DIM_STATES = 1
-const DIM_CONTROLS = 1
+const DIM_CONTROLS = 2
 const DIM_ALEAS = 1
 
 
@@ -177,11 +177,12 @@ end
 #Solve the problem and try nb_iter times to generate random data in case of infeasibility
 unsolve = true
 sol = 0
+firstControl = zeros(DIM_CONTROLS*N_SCENARIOS)
 i = 0
 nb_iter = 10
 
 while i<nb_iter
-    sol, status = extensive_formulation(model,params)
+    sol, firstControl, status = extensive_formulation(model,params)
     if (status == :Optimal)
         unsolve = false
         break
@@ -204,6 +205,7 @@ if (unsolve)
 else
     a,b = solve_dams(modelbis,paramsbis)
     println("solution =",sol)
+    println("firstControl =", firstControl)
     println("V0 = ", b[1].lambdas[1,:]*X0+b[1].betas[1])
 end
 

src/extensiveFormulation.jl

@@ -95,9 +95,10 @@ function extensive_formulation(model,
     solved = (status == :Optimal)
 
     if solved
-        return getObjectiveValue(mod), status
+        firstControl = collect(values(getValue(u)))[1:DIM_CONTROL*laws[1].supportSize]
+        return getObjectiveValue(mod), firstControl, status
     else
-        return -1., status
+        error("Extensive formulation not solved to optimality. Change the model")
     end
 
 end

test/runtests.jl

@@ -118,6 +118,15 @@ facts("SDDP algorithm: 1D case") do
     noise_scenarios = simulate_scenarios(model.noises,params.forwardPassNumber)
 
     sddp_costs = 0
+    
+    context("Unsolvable extensive formulation") do
+        model_ef = StochDynamicProgramming.LinearDynamicLinearCostSPmodel(n_stages, u_bounds,
+                                                                   x0, cost, dynamic, laws)
+        x_bounds_ef = [(-2., -1.)]
+        set_state_bounds(model_ef, x_bounds_ef)
+        @fact_throws extensive_formulation(model_ef, params)
+    end
+    
     context("Linear cost") do
         # Compute bellman functions with SDDP:
         V, pbs = solve_SDDP(model, params, 0)