Update benchmarks (#490)

odow · Nov 16, 2021 · 5ec8a2e · 5ec8a2e · odow · Dec 11, 2021
1 parent 182820d
commit 5ec8a2e
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Showing 9 changed files with 4 additions and 3 deletions.
diff --git a/benchmarks/benchmark.jl b/benchmarks/benchmark.jl
@@ -30,7 +30,8 @@ function benchmark(; kwargs...)
     # Precompile to avoid polluting the results!
     benchmark_file(joinpath(model_dir, models[1]); kwargs...)
     solutions = Dict{String,Any}(
-        benchmark_file(joinpath(model_dir, file); kwargs...) for file in models
+        file => benchmark_file(joinpath(model_dir, file); kwargs...) for
+        file in models
     )
     time = Dates.format(Dates.now(), "Y_mm_dd_HHMM_SS")
     data = Dict("date" => time, "solutions" => solutions)
@@ -114,7 +115,7 @@ filename_A = benchmark(
 filename_B = benchmark(
     time_limit = 60,
     stopping_rules = [SDDP.BoundStalling(10, 1e-6)],
-    duality_handler = SDDP.BanditDuality(),
+    duality_handler = SDDP.LagrangianDuality(),
 )
 
 report(filename_A, filename_B)
diff --git a/benchmarks/models/generation_expansion.sof.json.gz b/benchmarks/models/generation_expansion.sof.json.gz
diff --git a/benchmarks/models/sldp_example_two_2.sof.json.gz b/benchmarks/models/sldp_example_two_2.sof.json.gz
diff --git a/benchmarks/models/sldp_example_two_3.sof.json.gz b/benchmarks/models/sldp_example_two_3.sof.json.gz
diff --git a/benchmarks/models/sldp_example_two_6.sof.json.gz b/benchmarks/models/sldp_example_two_6.sof.json.gz
diff --git a/benchmarks/models/user_0001.sof.json.gz b/benchmarks/models/user_0001.sof.json.gz
diff --git a/benchmarks/models/vehicle_location.sof.json.gz b/benchmarks/models/vehicle_location.sof.json.gz
diff --git a/benchmarks/update.sh b/benchmarks/update.sh
diff --git a/docs/src/examples/sldp_example_two.jl b/docs/src/examples/sldp_example_two.jl
@@ -53,7 +53,7 @@ function sldp_example_two(; first_stage_integer::Bool = true, N = 2)
             joinpath(model_dir, "sldp_example_two_$(N).sof.json.gz");
             test_scenarios = 30,
         )
-        exit(0)
+        return
     end
     SDDP.train(model, iteration_limit = 100, log_frequency = 10)
     bound = SDDP.calculate_bound(model)