diff --git a/.gitignore b/.gitignore
index b9c4f32..1a6f574 100644
--- a/.gitignore
+++ b/.gitignore
@@ -131,4 +131,4 @@ dmypy.json
 # Pycharm
 .idea/
 
-gdplib/*/benchmark_result/
+gdplib/*/benchmark_result/*.log
diff --git a/benchmark.py b/benchmark.py
index 21dac5d..91f3abe 100644
--- a/benchmark.py
+++ b/benchmark.py
@@ -5,6 +5,8 @@
 from datetime import datetime
 from importlib import import_module
 from pyomo.environ import *
+import sys
+from contextlib import redirect_stdout
 
 
 def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
@@ -27,22 +29,25 @@ def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
     -------
     None
     """
+    # We clone the model to avoid the solver starting from the optimal solution from previous solve.
     model = model.clone()
-    stdout = sys.stdout
+
+    # Direct the solver output to a file
     if strategy in ["gdp.bigm", "gdp.hull"]:
-        transformation_start_time = time.time()
-        TransformationFactory(strategy).apply_to(model)
-        transformation_end_time = time.time()
-        with open(
-            result_dir + "/" + strategy + "_" + subsolver + ".log", "w"
-        ) as sys.stdout:
-            results = SolverFactory(subsolver).solve(
-                model, tee=True, timelimit=timelimit
-            )
-            results.solver.transformation_time = (
-                transformation_end_time - transformation_start_time
-            )
-            print(results)
+        with open(result_dir + "/" + strategy + "_" + subsolver + ".log", "w") as f:
+            with redirect_stdout(f):
+                transformation_start_time = time.time()
+                TransformationFactory(strategy).apply_to(model)
+                transformation_end_time = time.time()
+                results = SolverFactory(subsolver).solve(
+                    model,
+                    tee=True,
+                    add_options=["option reslim=3600;option threads=1;"],
+                )
+                results.solver.transformation_time = (
+                    transformation_end_time - transformation_start_time
+                )
+                print(results)
     elif strategy in [
         "gdpopt.enumerate",
         "gdpopt.loa",
@@ -50,21 +55,23 @@ def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
         "gdpopt.lbb",
         "gdpopt.ric",
     ]:
-        with open(
-            result_dir + "/" + strategy + "_" + subsolver + ".log", "w"
-        ) as sys.stdout:
-            results = SolverFactory(strategy).solve(
-                model,
-                tee=True,
-                nlp_solver=subsolver,
-                mip_solver=subsolver,
-                minlp_solver=subsolver,
-                local_minlp_solver=subsolver,
-                time_limit=timelimit,
-            )
-            print(results)
+        with open(result_dir + "/" + strategy + "_" + subsolver + ".log", "w") as f:
+            with redirect_stdout(f):
+                results = SolverFactory(strategy).solve(
+                    model,
+                    tee=True,
+                    nlp_solver=subsolver,
+                    nlp_solver_args=dict(add_options=["option threads=1;"]),
+                    mip_solver=subsolver,
+                    mip_solver_args=dict(add_options=["option threads=1;"]),
+                    minlp_solver=subsolver,
+                    minlp_solver_args=dict(add_options=["option threads=1;"]),
+                    local_minlp_solver=subsolver,
+                    local_minlp_solver_args=dict(add_options=["option threads=1;"]),
+                    time_limit=timelimit,
+                )
+                print(results)
 
-    sys.stdout = stdout
     with open(result_dir + "/" + strategy + "_" + subsolver + ".json", "w") as f:
         json.dump(results.json_repn(), f)
     return None
@@ -73,20 +80,23 @@ def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
 if __name__ == "__main__":
     instance_list = [
         # "batch_processing",
-        # "biofuel",
-        # "disease_model",
-        # "gdp_col",
-        # "hda",
+        # "biofuel", # enumeration got stuck
+        # "cstr",
+        "disease_model",
+        "ex1_linan_2023",
+        "gdp_col",
+        "hda",
         "jobshop",
         # "kaibel",
-        # "positioning",
-        # "spectralog",
-        # "med_term_purchasing",
-        # "methanol",
-        # "mod_hens",
-        # "modprodnet",
-        # "stranded_gas",
-        # "syngas",
+        "med_term_purchasing",
+        "methanol",
+        "mod_hens",
+        "modprodnet",
+        "positioning",
+        "small_batch",
+        "spectralog",
+        "stranded_gas",
+        "syngas",
     ]
     strategy_list = [
         "gdp.bigm",
@@ -95,16 +105,22 @@ def benchmark(model, strategy, timelimit, result_dir, subsolver="scip"):
         "gdpopt.loa",
         "gdpopt.gloa",
         "gdpopt.ric",
+        "gdpopt.lbb",
     ]
     current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
-    timelimit = 600
+    timelimit = 3600
 
     for instance in instance_list:
-        print("Benchmarking instance: " + instance)
         result_dir = "gdplib/" + instance + "/benchmark_result/"
         os.makedirs(result_dir, exist_ok=True)
 
+        print("Benchmarking instance: ", instance)
         model = import_module("gdplib." + instance).build_model()
 
         for strategy in strategy_list:
-            benchmark(model, strategy, timelimit, result_dir)
+            if os.path.exists(result_dir + "/" + strategy + "_" + "gams" + ".json"):
+                continue
+            try:
+                benchmark(model, strategy, timelimit, result_dir, "gams")
+            except:
+                pass