diff --git a/.mypy.ini b/.mypy.ini
index 1abcf2c..0c16ac8 100644
--- a/.mypy.ini
+++ b/.mypy.ini
@@ -1,5 +1,8 @@
 [mypy]
 
+[mypy-graph_tool.*]
+ignore_missing_imports=True
+
 [mypy-networkx.*]
 ignore_missing_imports = True
 
diff --git a/.travis.yml b/.travis.yml
index 4e00c61..dc0ec54 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -10,6 +10,20 @@ before_install:
   - git clone https://github.com/bcamath-ds/OPLib.git ../OPLib
   - git clone https://github.com/rhgrant10/tsplib95.git ../tsplib95
 install:
+  # install conda
+  - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
+  - bash miniconda.sh -b -p $HOME/miniconda
+  - source "$HOME/miniconda/etc/profile.d/conda.sh"
+  - hash -r
+  - conda config --set always_yes yes --set changeps1 no
+  - conda update -q conda
+  - conda info -a
+  # create conda env and activate
+  - conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION
+  - conda activate test-environment
+  # install graph tool
+  - conda install -c conda-forge graph-tool
+  # install our package
   - pip install .
   - pip install -r requirements.txt
 script:
diff --git a/setup.py b/setup.py
index a8eb073..4259e35 100644
--- a/setup.py
+++ b/setup.py
@@ -9,7 +9,7 @@
     description="Library of instances for TSP with Profits",
     install_requires=[
         "pandas>=1.0.0",
-        "tsplib95",
+        "tsplib95>=0.7.1",
     ],
     name="tspwplib",
     packages=["tspwplib"],
diff --git a/tests/test_profits_problem.py b/tests/test_profits_problem.py
index eb8647c..1192ca5 100644
--- a/tests/test_profits_problem.py
+++ b/tests/test_profits_problem.py
@@ -81,3 +81,36 @@ def test_get_graph(oplib_root, generation, graph_name, alpha):
             assert type(value) in valid_types
 
     assert graph.graph["root"] == 1
+
+
+def test_get_graph_tool(oplib_root, generation, graph_name, alpha):
+    """Test returning graph tool undirected weighted graph"""
+    filepath = build_path_to_oplib_instance(
+        oplib_root, generation, graph_name, alpha=alpha
+    )
+    problem = ProfitsProblem.load(filepath)
+    gt_graph = problem.get_graph_tool()
+    nx_graph = problem.get_graph(normalize=True)
+    assert nx_graph.has_node(0)
+    assert 0 in gt_graph.get_vertices()
+    assert gt_graph.num_vertices() == nx_graph.number_of_nodes()
+    assert gt_graph.num_edges() == nx_graph.number_of_edges()
+
+    # check weight
+    for u, v, data in nx_graph.edges(data=True):
+        gt_edge = gt_graph.edge(u, v, add_missing=False)
+        assert gt_edge
+        assert gt_graph.ep.weight[gt_edge] == data["weight"]
+    # check prize on vertices
+    for u, data in nx_graph.nodes(data=True):
+        assert data["prize"] == gt_graph.vertex_properties.prize[u]
+
+
+def test_get_root_vertex(oplib_root, generation, graph_name, alpha):
+    """Test the root vertex is 1 when un-normalized (0 when normalized)"""
+    filepath = build_path_to_oplib_instance(
+        oplib_root, generation, graph_name, alpha=alpha
+    )
+    problem = ProfitsProblem.load(filepath)
+    assert problem.get_root_vertex(normalize=False) == 1
+    assert problem.get_root_vertex(normalize=True) == 0
diff --git a/tspwplib/problem.py b/tspwplib/problem.py
index 53d2602..dfa65d0 100644
--- a/tspwplib/problem.py
+++ b/tspwplib/problem.py
@@ -1,9 +1,10 @@
 """Functions and classes for datasets"""
 
 from typing import List
+import graph_tool as gt
 import networkx as nx
 import tsplib95
-from .types import Vertex, VertexFunctionName, VertexLookup
+from .types import Vertex, VertexLookup
 
 
 class ProfitsProblem(tsplib95.models.StandardProblem):
@@ -32,11 +33,11 @@ def __set_graph_attributes(self, graph: nx.Graph) -> None:
         graph.graph["type"] = self.type
         graph.graph["dimension"] = self.dimension
         graph.graph["capacity"] = self.capacity
-        # pylint: disable=unsubscriptable-object
-        graph.graph["root"] = self.depots[0]
+        graph.graph["root"] = self.get_root_vertex()
 
     def __set_node_attributes(self, graph: nx.Graph, names: VertexLookup) -> None:
         """Add node attributes"""
+        node_score = self.get_node_score()
         for vertex in list(self.get_nodes()):
             # NOTE pyintergraph cannot handle bool, so we remove some attributes:
             # is_depot, demand, display
@@ -47,6 +48,7 @@ def __set_node_attributes(self, graph: nx.Graph, names: VertexLookup) -> None:
                 names[vertex],
                 x=coord[0],
                 y=coord[1],
+                prize=node_score[vertex],
                 # is_depot=is_depot,
             )
             # demand: int = self.demands.get(vertex)
@@ -55,9 +57,9 @@ def __set_node_attributes(self, graph: nx.Graph, names: VertexLookup) -> None:
             # graph[vertex]["demand"] = demand
             # if not display is None:
             # graph[vertex]["display"] = display
-        nx.set_node_attributes(
-            graph, self.get_node_score(), name=VertexFunctionName.prize
-        )
+        # nx.set_node_attributes(
+        #     graph, self.get_node_score(), name=VertexFunctionName.prize
+        # )
 
     def get_graph(self, normalize: bool = False) -> nx.Graph:
         """Return a networkx graph instance representing the problem.
@@ -82,6 +84,41 @@ def get_graph(self, normalize: bool = False) -> nx.Graph:
         self.__set_edge_attributes(graph, names)
         return graph
 
+    def get_graph_tool(self, normalize: bool = True) -> gt.Graph:
+        """Return a graph tools undirected graph
+
+        Args:
+            normalize: rename nodes to be zero-indexed
+        """
+        graph = gt.Graph(directed=not self.is_symmetric())
+
+        # by default normalize because graph tools index starts at zero
+        nodes: List[Vertex] = list(self.get_nodes())
+        if normalize:
+            names = {n: i for i, n in enumerate(nodes)}
+        else:
+            names = {n: n for n in nodes}
+
+        # create list of edges
+        edges = []
+        for u, v in self.get_edges():
+            if u <= v or not self.is_symmetric():
+                edges.append((names[u], names[v], self.get_weight(u, v)))
+
+        # assign weight to edges
+        weight_property = graph.new_edge_property("int")
+        graph.add_edge_list(edges, eprops=[weight_property])
+        graph.ep.weight = weight_property
+
+        # assign prize to vertices
+        prize_property = graph.new_vertex_property("int")
+        node_score = self.get_node_score()
+        prize_list = [node_score[v + 1] for v in graph.get_vertices()]
+        prize_property.a = prize_list
+        graph.vertex_properties.prize = prize_property
+
+        return graph
+
     def get_cost_limit(self) -> int:
         """Get the cost limit for a TSP with Profits problem
 
@@ -105,3 +142,26 @@ def get_tsp_optimal_value(self) -> int:
             TSP optimal value
         """
         return self.tspsol
+
+    def get_root_vertex(self, normalize: bool = False) -> Vertex:
+        """Get the root vertex
+
+        Args:
+            normalize: If true, vertices start at index 0
+
+        Returns:
+            The first depot in the list
+
+        Raises:
+            ValueError: If the list of depots is empty
+        """
+        nodes: List[Vertex] = list(self.get_nodes())
+        if normalize:
+            names = {n: i for i, n in enumerate(nodes)}
+        else:
+            names = {n: n for n in nodes}
+        try:
+            # pylint: disable=unsubscriptable-object
+            return names[self.depots[0]]
+        except KeyError as key_error:
+            raise ValueError("The list of depots is empty") from key_error