# List of NP-complete problems

# This is a list of some of the more commonly known problems that are NP-complete when expressed as decision problems. As there are hundreds of such problems known, this list is in no way comprehensive. Many problems of this type can be found in Garey & Johnson (1979).

## Graphs and hypergraphs

Graphs occur frequently in everyday applications. Examples include biological or social networks, which contain hundreds, thousands and even billions of nodes in some cases (e.g. Facebook or LinkedIn).

- 1-planarity
^{[1]} - 3-dimensional matching
^{[2]}^{[3]} - Bipartite dimension
^{[4]} - Capacitated minimum spanning tree
^{[5]} - Route inspection problem (also called
**Chinese postman problem**) for mixed graphs (having both directed and undirected edges). The program is solvable in polynomial time if the graph has all undirected or all directed edges. Variants include the rural postman problem.^{[6]} - Clique problem
^{[2]}^{[7]} - Complete coloring, a.k.a. achromatic number
^{[8]} - Domatic number
^{[9]} - Dominating set, a.k.a. domination number
^{[10]}

- NP-complete special cases include the edge dominating set problem, i.e., the dominating set problem in line graphs. NP-complete variants include the connected dominating set problem and the maximum leaf spanning tree problem.
^{[11]}

- NP-complete special cases include the edge dominating set problem, i.e., the dominating set problem in line graphs. NP-complete variants include the connected dominating set problem and the maximum leaf spanning tree problem.

- Bandwidth problem
^{[12]} - Clique cover problem
^{[2]}^{[13]} - Rank coloring a.k.a. cycle rank
- Degree-constrained spanning tree
^{[14]} - Exact cover problem. Remains NP-complete for 3-sets. Solvable in polynomial time for 2-sets (this is amatching).
^{[2]}^{[15]} - Feedback vertex set
^{[2]}^{[16]} - Feedback arc set
^{[2]}^{[17]} - Graph homomorphism problem
^{[18]} - Graph coloring
^{[2]}^{[19]} - Graph partition into subgraphs of specific types (triangles, isomorphic subgraphs, Hamiltonian subgraphs,forests, perfect matchings) are known NP-complete. Partition into cliques is the same problem as coloringthe complement of the given graph. A related problem is to find a partition that is optimal terms of the number of edges between parts.
^{[20]} - Hamiltonian completion
^{[21]} - Hamiltonian path problem, directed and undirected.
^{[2]}^{[22]} - Longest path problem
^{[23]} - Maximum bipartite subgraph or (especially with weighted edges) maximum cut.
^{[2]}^{[24]} - Maximum independent set
^{[25]} - Maximum Induced path
^{[26]} - Graph intersection number
^{[27]} - Metric dimension of a graph
^{[28]} - Minimum k-cut
- Minimum spanning tree, or Steiner tree, for a subset of the vertices of a graph.
^{[2]}(The minimum spanning tree for an entire graph is solvable in polynomial time.) - Pathwidth
^{[29]} - Set cover (also called
**minimum cover**problem) This is equivalent, by transposing the incidence matrix, to the hitting set problem.^{[2]}^{[30]} - Set splitting problem
^{[31]} - Shortest total path length spanning tree
^{[32]} - Slope number two testing
^{[33]} - Treewidth
^{[29]} - Vertex cover
^{[2]}^{[34]}

## Mathematical programming

- 3-partition problem
^{[35]} - Bin packing problem
^{[36]} - Knapsack problem, quadratic knapsack problem, and several variants
^{[2]}^{[37]} - Variations on the Traveling salesman problem. The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric.
^{[38]} - Bottleneck traveling salesman
^{[39]} - Integer programming. The variant where variables are required to be 0 or 1, called zero-one linear programming, and several other variants are also NP-complete
^{[2]}^{[40]} - Latin squares (The problem of determining if a partially filled square can be completed to form one)
- Numerical 3-dimensional matching
^{[41]} - Partition problem
^{[2]}^{[42]} - Quadratic assignment problem
^{[43]} - Quadratic programming (NP-hard in some cases, P if convex)
- Subset sum problem
^{[44]}

## Formal languages and string processing

- Closest string
^{[45]} - Longest common subsequence problem
^{[46]} - The bounded variant of the Post correspondence problem
^{[47]} - Shortest common supersequence
^{[48]} - String-to-string correction problem
^{[49]}

## Games and puzzles

- Battleship
- Bejeweled
^{[50]} - Bulls and Cows, marketed as Master Mind: certain optimisation problems but not the game itself.
- Candy Crush Saga
^{[50]}^{[51]} - Donkey Kong
^{[52]} - Eternity II
- (Generalized) FreeCell
^{[53]} - Fillomino
^{[54]} - Hashiwokakero
^{[55]} - Heyawake
^{[56]} - (Generalized) Instant Insanity
^{[57]} - Kakuro (Cross Sums)
- Kuromasu (also known as Kurodoko)
^{[58]} - Legend of Zelda
^{[52]} - Lemmings (with a polynomial time limit)
^{[59]} - Light Up
^{[60]} - Masyu
^{[61]} - Metroid
^{[52]} - Minesweeper Consistency Problem
^{[62]}(but see Scott, Stege, & van Rooij^{[63]}) - Nimber (or Grundy number) of a directed graph.
^{[64]} - Nonograms
- Nurikabe
- Pokémon
^{[52]} - SameGame
- Slither Link on a variety of grids
^{[65]}^{[66]}^{[67]} - (Generalized) Sudoku
^{[65]}^{[68]} - Super Mario Bros
^{[52]} - Problems related to Tetris
^{[69]} - Verbal arithmetic

## Other

- Art gallery problem and its variations.
- Berth allocation problem
^{[70]} - Betweenness
- Assembling an optimal Bitcoin block.
^{[71]} - Boolean satisfiability problem (SAT).
^{[2]}^{[72]}There are many variations that are also NP-complete. An important variant is where each clause has exactly three literals (3SAT), since it is used in the proof of many other NP-completeness results.^{[73]} - Conjunctive Boolean query
^{[74]} - Cyclic ordering
- Circuit satisfiability problem
- Uncapacitated Facility Location
- Flow Shop Scheduling Problem
- Generalized assignment problem
- Upward planarity testing
^{[33]} - Hospitals-and-residents problem with couples
- Some problems related to Job-shop scheduling
- Monochromatic triangle
^{[75]} - Minimum maximal independent set a.k.a. minimum independent dominating set
^{[76]}

- NP-complete special cases include the minimum maximal matching problem,
^{[77]}which is essentially equal to the edge dominating set problem (see above).

- NP-complete special cases include the minimum maximal matching problem,

- Maximum common subgraph isomorphism problem
^{[78]} - Minimum degree spanning tree
- Minimum k-spanning tree
- Metric k-center
- Maximum 2-Satisfiability
^{[79]} - Modal logic S5-Satisfiability
- Some problems related to Multiprocessor scheduling
- Maximum volume submatrix – Problem of selecting the best conditioned subset of a larger m x n matrix. This class of problem is associated with Rank revealing QR factorizations and D optimal experimental design.
^{[80]} - Minimal addition chains for sequences.
^{[81]}The complexity of minimal addition chains for individual numbers is unknown.^{[82]} - Non-linear univariate polynomials over GF[2
^{n}], n the length of the input. Indeed, over any GF[q^{n}]. - Open-shop scheduling
- Pathwidth,
^{[29]}or, equivalently, interval thickness, and vertex separation number^{[83]} - Pancake sorting distance problem for strings
^{[84]} - k-Chinese postman
- Subgraph isomorphism problem
^{[85]} - Variations of the Steiner tree problem. Specifically, with the discretized Euclidean metric, rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric.
^{[86]} - Set packing
^{[2]}^{[87]} - Serializability of database histories
^{[88]} - Scheduling to minimize weighted completion time
- Sparse approximation
- Block Sorting
^{[89]}(Sorting by Block Moves) - Second order instantiation
- Treewidth
^{[29]} - Testing whether a tree may be represented as Euclidean minimum spanning tree
- Three-dimensional Ising model
^{[90]} - Vehicle routing problem