bugfix

Author: BatyLeo

src/DynamicVehicleScheduling/anticipative_solver.jl

@@ -51,12 +51,13 @@ function anticipative_solver(
     nb_epochs=typemax(Int),
     seed=get_seed(env),
 )
-    reset_env && reset!(env; reset_rng=true, seed)
+    if reset_env
+        reset!(env; reset_rng=true, seed)
+    end
 
     start_epoch = current_epoch(env)
     end_epoch = min(last_epoch(env), start_epoch + nb_epochs - 1)
     T = start_epoch:end_epoch
-    @info T
 
     request_epoch = [0]
     for t in T
@@ -70,7 +71,7 @@ function anticipative_solver(
     (; epoch_duration, Δ_dispatch) = env.instance
 
     model = model_builder()
-    # set_silent(model)
+    set_silent(model)
 
     nb_nodes = length(customer_index)
     job_indices = 2:nb_nodes
@@ -129,11 +130,44 @@ function anticipative_solver(
 
     optimize!(model)
 
-    @info "Objective value: $(JuMP.objective_value(model))"
-    @info termination_status(model)
-    y_val = value.(y)
-    @info sum(y_val[j, 2, t] for j in 1:nb_nodes, t in epoch_indices)
-
+    # Debug infeasibility
+    if termination_status(model) == JuMP.MOI.INFEASIBLE
+        @warn "Model is infeasible! Let's debug..."
+        @info "Number of nodes: $nb_nodes"
+        @info "Number of job indices: $(length(job_indices))"
+        @info "Epoch indices: $epoch_indices"
+        @info "Request epochs: $request_epoch"
+        @info "Start times: $start_time"
+        @info "Service times: $service_time"
+        @info "Epoch duration: $epoch_duration, Δ_dispatch: $Δ_dispatch"
+
+        # Check if any job can be scheduled in any epoch
+        for i in job_indices
+            can_schedule = false
+            for t in epoch_indices
+                # Check release constraint
+                if t >= request_epoch[i]
+                    # Check time limit constraint
+                    travel_time = duration[1, i]
+                    arrival_time = (t - 1) * epoch_duration + Δ_dispatch + travel_time
+                    if arrival_time <= start_time[i]
+                        can_schedule = true
+                        @info "Job $i can be scheduled in epoch $t (arrival: $arrival_time <= deadline: $(start_time[i]))"
+                        break
+                    else
+                        @info "Job $i cannot be scheduled in epoch $t: arrival $arrival_time > deadline $(start_time[i])"
+                    end
+                else
+                    @info "Job $i cannot be scheduled in epoch $t: request epoch $(request_epoch[i]) > epoch $t"
+                end
+            end
+            if !can_schedule
+                @warn "Job $i cannot be scheduled in any epoch! Request epoch: $(request_epoch[i]), start time: $(start_time[i]), travel time: $(duration[1, i]), release index $(customer_index[i])"
+                @warn "  Epochs available: $epoch_indices"
+                @warn "  Epoch duration: $epoch_duration, Δ_dispatch: $Δ_dispatch"
+            end
+        end
+    end
     obj = JuMP.objective_value(model)
     epoch_routes = retrieve_routes_anticipative(
         value.(y), env, customer_index, epoch_indices

src/DynamicVehicleScheduling/instance.jl

@@ -31,7 +31,7 @@ function Instance(
             maximum(static_instance.start_time) - minimum(static_instance.duration[1, :]) -
             Δ_dispatch
         ) / epoch_duration,
-    )
+    ) - 1
     return Instance(;
         static_instance=static_instance,
         max_requests_per_epoch=max_requests_per_epoch,

src/DynamicVehicleScheduling/plot.jl

@@ -476,11 +476,38 @@ function animate_epochs(
         (0.0, 1.0)
     end
 
-    # Create animation with alternating state and route frames
-    anim = @animate for frame_idx in 1:(2*n_epochs)
-        epoch_idx = ceil(Int, frame_idx / 2)
-        is_route_frame = (frame_idx % 2 == 0)
+    # Helper function to check if routes exist and are non-empty
+    function has_routes(routes)
+        if isnothing(routes)
+            return false
+        elseif routes isa Vector{Vector{Int}}
+            return any(!isempty(route) for route in routes)
+        elseif routes isa Vector{Int}
+            return !isempty(routes)
+        elseif routes isa BitMatrix
+            return any(routes)
+        else
+            return false
+        end
+    end
 
+    # Create frame plan: determine which epochs have routes
+    frame_plan = []
+    for (epoch_idx, sample) in enumerate(data_samples)
+        # Always add state frame
+        push!(frame_plan, (epoch_idx, :state))
+
+        # Add routes frame only if routes exist
+        if has_routes(sample.y_true)
+            push!(frame_plan, (epoch_idx, :routes))
+        end
+    end
+
+    total_frames = length(frame_plan)
+
+    # Create animation with dynamic frame plan
+    anim = @animate for frame_idx in 1:total_frames
+        epoch_idx, frame_type = frame_plan[frame_idx]
         sample = data_samples[epoch_idx]
         state = sample.instance
 
@@ -498,7 +525,7 @@ function animate_epochs(
                 kwargs...
             )
         else
-            if is_route_frame && !isnothing(sample.y_true)
+            if frame_type == :routes
                 # Show state with routes
                 plot_routes(state, sample.y_true;
                            xlims=xlims,
@@ -514,7 +541,7 @@ function animate_epochs(
                            show_route_labels=false,
                            size=figsize,
                            kwargs...)
-            else
+            else # frame_type == :state
                 # Show state only
                 plot_state(state;
                           xlims=xlims,

test/dynamic_assortment.jl

@@ -272,7 +272,7 @@ end
     b = DynamicAssortmentBenchmark(N=5, d=2, K=3, max_steps=20)
 
     # Generate test data
-    dataset = generate_dataset(b, 5; seed=0)
+    dataset = generate_dataset(b, 10; seed=0)
     environments = generate_environments(b, dataset)
 
     # Get policies
@@ -284,8 +284,8 @@ end
     @test greedy.name == "Greedy"
 
     # Test policy evaluation
-    r_expert, d = evaluate_policy!(expert, environments)
-    r_greedy, _ = evaluate_policy!(greedy, environments)
+    r_expert, d = evaluate_policy!(expert, environments, 10)
+    r_greedy, _ = evaluate_policy!(greedy, environments, 10)
 
     @test length(r_expert) == length(environments)
     @test length(r_greedy) == length(environments)