diff --git a/.gitignore b/.gitignore
index bf3e102..a47f070 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,7 @@
 *.jl.*.cov
 *.jl.cov
 *.jl.mem
-/Manifest.toml
+Manifest.toml
 lib
 .vscode
 Artifact
diff --git a/examples/combinatorial-optimization/Project.toml b/examples/combinatorial-optimization/Project.toml
new file mode 100644
index 0000000..01586a8
--- /dev/null
+++ b/examples/combinatorial-optimization/Project.toml
@@ -0,0 +1,13 @@
+[deps]
+CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+CuTropicalGEMM = "c2b282c3-c9c2-431d-80f7-a1a0561ebe55"
+GenericTensorNetworks = "3521c873-ad32-4bb4-b63d-f4f178f42b49"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+TropicalNumbers = "b3a74e9c-7526-4576-a4eb-79c0d4c32334"
+
+[compat]
+CUDA = "5"
+CuTropicalGEMM = "0.1"
+GenericTensorNetworks = "1"
+TropicalNumbers = "0.6"
+julia = "1.9"
diff --git a/examples/combinatorial-optimization/README.md b/examples/combinatorial-optimization/README.md
new file mode 100644
index 0000000..f476289
--- /dev/null
+++ b/examples/combinatorial-optimization/README.md
@@ -0,0 +1,8 @@
+# Solving combinatorial optimization problem with generic tensor networks
+
+## Problem description
+
+We consider solving the maximum independent set problem. Please check [the manual page](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/IndependentSet/) of package [GenericTensorNetworks.jl](https://github.com/QuEraComputing/GenericTensorNetworks.jl) [1] for a detailed description of the problem.
+
+## References
+1. Liu, J.-G., Gao, X., Cain, M., Lukin, M. D. & Wang, S.-T. Computing solution space properties of combinatorial optimization problems via generic tensor networks. Preprint at https://doi.org/10.48550/arXiv.2205.03718 (2022).
diff --git a/examples/combinatorial-optimization/main.jl b/examples/combinatorial-optimization/main.jl
new file mode 100644
index 0000000..cc0457a
--- /dev/null
+++ b/examples/combinatorial-optimization/main.jl
@@ -0,0 +1,22 @@
+using GenericTensorNetworks, CUDA, TropicalNumbers, GenericTensorNetworks.Graphs
+using CuTropicalGEMM
+using Random; Random.seed!(2)
+
+# Create a random 3-regular graph
+g = GenericTensorNetworks.random_diagonal_coupled_graph(38, 38, 0.8)
+
+# Create a tensor network representation for the independent set problem on this graph
+# Let us specify the tensor network contraction order optimizer to be TreeSA, which is a local search algorithm
+tn = IndependentSet(g; optimizer=TreeSA(ntrials=1, niters=5))
+
+# Let us check its contraction complexity
+contraction_complexity(tn)
+
+# Let us find the maximum independent set using the tensor network contraction.
+# It will use the CuTropicalGEMM library to perform the contraction.
+# Please use Float32 type for the best performance.
+@time Array(solve(tn, SizeMax(); usecuda=true, T=Float32))
+# output: 1.1s
+
+# If you want to use the automatic differentiation based approach to find the optimal solution.
+@time solve(tn, SingleConfigMax(; bounded=true); usecuda=true, T=Float32)
\ No newline at end of file