Hamiltonian Cycles and paths by SanjuDudeja

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Analysis and Design of Algorithms

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									Hamiltonian Cycles and paths

          Bin Zhou
• Hamiltonian cycle (HC): is a cycle which
  passes once and exactly once through every
  vertex of G (G can be digraph).
• Hamiltonian path: is a path which passes
  once and exactly once through every vertex
  of G (G can be digraph).
• A graph is Hamiltonian iff a Hamiltonian
  cycle (HC) exists.
• Invented by Sir William Rowan Hamilton
  in 1859 as a game
• Since 1936, some progress have been made
• Such as sufficient and necessary conditions
  be given
• G.A. Dirac, 1952,
 If G is a simple graph with n(>=3) vertices, and if the
 degree of each is at least 1/2n, then G is Hamiltonian
• O.Ore , 1960
 If G is a simple graph with n(>=3) vertices, and if the sum
 of the degrees of each pair of non-adjacent vertices is at
 least n, then G is Hamiltonian
• Bondy and Chvatal , 1976
  For G to be Hamiltonian, it is necessary and
  sufficient that [G]n be Hamiltonian. ([G]n is
  gotten from G by adding edges joining non-
  adjacent vertices whose sum of degrees is
  equal to, or greater than n)
• Fraudee, Dould, Jacobsen, Schelp (1989)
   If G is a 2-connected graph such that for
  every pair of nonadjacent nodes u and v,
  then G is Hamiltonian
• Hamiltonian cycles in fault random
  geometric network
• In a network, if Hamiltonian cycles exist,
  the fault tolerance is better.
   Hamiltonian problem is NPC
• This is a well known NP complete problem
• For general graph, we can not find an
  exactly linear time complexity algorithm to
  find a Hamiltonian cycle or path
                   HC algorithms
• For general graphs, no efficient algorithm
 NP-complete for perfect graphs, planar bipartite graphs,
 grid graphs, 3-connected planar graphs
• For some special graphs, exist efficient
  N. Ghiba, T. Nishizeki (1989)
  Polynomial algorithm for 4-connected planar graphs.
 G.Gutin (1997)
  Polynomial algorithm for quasi-transitive digraphs
     Some Algorithms for HC
• L. Pósa (1976)
  Rotational transformation
• B. Bollobás, T.I.Fenner, and A. M. Frieze
  Cycle extension (HAM) (1987)
• Silvano Martello
  Algorithm 595 (1983)
    Two classes of algorithms
• Heuristic algorithm
   Pósa, UHC, DHC, HAM, etc
• Backtrack algorithm
   595HAM, KTC, MultiPath
            Backtrack Algorithm
• Recurse(Path p, endpoint e)
• While (e has unvisited neighbors)
  { GetNewNode x; (add x node to P)
    PruneGraph. (Prune graph. If result graph does not permit a HC
  forming, remove x from P and continue)
   FormCycle (If P includes all nodes then try to form cycle. Fail,
  remove x and continue; Succ, return success)
    BackTrack: Recurse(P,x)
   Return fail.
         Backtrack Algorithm
• Search all the potential solutions
• Employ pruning of some kind to restrict the
  amount of researching
• Advantage:
 Find all solution, can decide HC exists or not
• Disadvantage
  Worst case, needs exponential time. Normally,
  take a long time
            Heuristic Algorithm
Initialize path P
While {
  Find new unvisited node.
  If found { Extend path P and pruning on the graph. If this
   choice does not permit HC, remove the extended node.
  } else
    Transform Path. Try all possible endpoints of this path
    Form cycle. Try to find HC
         Heuristic Algorithm
• Advantage:
   Fast. Linear or low-order polynomial time
• Disadvantage
   Maybe can not find the HC
      Ham heuristic algorithm
• Try to extend existing path and never
  decrease the path length
• Do cycle extension
• Do rotational transformation
                   Ham algorithm
Start from a random node and find a neighbor to get a path P. |P|=2
Do {
  Change partial path array A. oldlength=|P|.
  While |P|==oldlength {
     Find neighbors of P’s endpoints.Try to extend P.
     For (each neighbor) do {
        If Extendable
           Extend and continue;
          Do cycle extension or rotational transformation; }
        Check termination condition and change P
           Cycle Extention

Path P:
                x1        xi        xi+1          xk


Path P’:
           xi        x1        xk          xi+1        u
Rotational transformation

Path P:
           x1    xi          xi+1        xk

Path P’:
           xi   x1    xi+1          xk
                                        Node 20
% Hamiltonian cycle

                            0   2        4        6   8
                                    Mean degree
                                          Nodes 50
% Have Hamiltonian cycle





                                 0   2    4      6     8   10
                                         Mean degree
                                    Node 100

% Hamiltonian Cycle

                            0   5        10    15
                                Mean degree
• The program can not check large graph due
  to the memory restriction
• May be need more conditions to decide the
  probability of HC exists
• We can solve large problem using parallel

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