skip to main content
research-article

Solving problems on recursively constructed graphs

Published:15 January 2009Publication History
Skip Abstract Section

Abstract

Fast algorithms can be created for many graph problems when instances are confined to classes of graphs that are recursively constructed. This article first describes some basic conceptual notions regarding the design of such fast algorithms, and then the coverage proceeds through several recursive graph classes. Specific classes include trees, series-parallel graphs, k-terminal graphs, treewidth-k graphs, k-trees, partial k-trees, k-jackknife graphs, pathwidth-k graphs, bandwidth-k graphs, cutwidth-k graphs, branchwidth-k graphs, Halin graphs, cographs, cliquewidth-k graphs, k-NLC graphs, k-HB graphs, and rankwidth-k graphs. The definition of each class is provided. Typical algorithms are applied to solve problems on instances of most classes. Relationships between the classes are also discussed.

References

  1. Amir, E. 2001. Efficient approximation for triangulation of minimum treewidth. In Proceedings of the 17th Conference on Uncertainty in Artificial Intelligence, 7--15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Arnborg, S. 1985. Efficient algorithms for combinatorial problems on graphs with bounded decomposibility: A survey. Bit 25, 2--23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Arnborg, S., Corneil, D., and Proskurowski, A. 1987. Complexity of finding embeddings in a k-tree. SIAM J. Algebr. Discrete Methods 8, 277--284. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Arnborg, S., Courcelle, B., Proskurowski, A., and Seese, D. 1993. An algebraic theory of graph reductions. J. ACM 40, 1134--1164. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Arnborg, S., Hedetniemi, S., and Proskurowski, A. 1994. Efficient algorithms and partial k-trees. Discrete Appl. Math. 54, 2--3. Guest editors of special issue.Google ScholarGoogle Scholar
  6. Arnborg, S., Lagergren, J., and Seese, D. 1991. Easy problems for tree-decomposable graphs. J. Algor. 12, 308--340. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Arnborg, S. and Proskurowski, A. 1985. Characterization and recognition of partial k-trees. Congressus Numer. 47, 69--75.Google ScholarGoogle Scholar
  8. Arnborg, S. and Proskurowski, A. 1986. Characterization and recognition of partial 3-trees. SIAM J. Algebr. Discrete Methods 7, 305--314. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Arnborg, S. and Proskurowski, A. 1989. Linear time algorithms for NP-hard problems restricted to partial k-trees. Discrete Appl. Math. 23, 11--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Arnborg, S., Proskurowski, A., and Corneil, D. 1990. Forbidden minors characterization of partial 3-trees. Discrete Math. 80, 1--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Babel, L. and Olariu, S. 1998. On the structure of graphs with few P4s. Discrete Appl. Math. 84, 1--13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Bachoore, E. and Bodlaender, H. 2006. A branch-and-bound algorithm for exact, upper, and lower bounds on treewidth. In Proceedings of the 2nd International Conference on Algorithmic Aspects in Information and Management. Lecture Notes in Computer Science, vol. 4041. Springer, 255--266.Google ScholarGoogle Scholar
  13. Becker, A. and Geiger, D. 2001. A sufficiently fast algorithm for finding close to optimal clique trees. Artif. Intell. 125, 3--17. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Beineke, L. and Pippert, R. 1971. Properties and characterizations of k-trees. Math. 18, 141--151.Google ScholarGoogle Scholar
  15. Bern, M., Lawler, E., and Wong, A. 1987. Linear time computation of optimal subgraphs of decomposable graphs. J. Algor. 8, 216--235. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Bienstock, D., Robertson, N., Seymour, P., and Thomas, R. 1991. Quickly excluding a forest. J. Combinatorial Theory Series B 52, 274--283. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Blair, J., Heggernes, P., and Telle, J. 2001. A practical algorithm for making filled graphs minimal. Theor. Comput. Sci. 250, 125--141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Bodlaender, H. 1987. Dynamic programming on graphs with bounded tree-width. Tech. Rep., Massachusetts Institute of Technology.Google ScholarGoogle Scholar
  19. Bodlaender, H. 1988. Dynamic programming algorithms on graphs with bounded tree-width. In Proceedings of the 15th International Colloquium on Automata, Languages and Programming. Lecture Notes in Computer Science, vol. 317. Springer, 105--109. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Bodlaender, H. 1990. Polynomial algorithms for graph isomorphism and chromatic index on partial k-trees. J. Algor. 11, 631--643. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Bodlaender, H. 1993. A tourist guide through treewidth. Acta Cybernetica 11, 1--23.Google ScholarGoogle Scholar
  22. Bodlaender, H. 1996. A linear-time algorithm for finding tree decompositions of small treewidth. SIAM J. Comput. 25, 1305--1317. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Bodlaender, H. 1998. A partial k-arboretum of graphs with bounded treewidth. Theor. Comput. Sci. 209, 1--45. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Bodlaender, H., Fomin, F., Koster, A., Kratsch, D., and Thilikos, D. 2006. On exact algorithms for treewidth. In Proceedings of the 14th Annual European Symposium on Algorithms. Lecture Notes in Computer Science, vol. 4168. Springer, 672--683. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Bodlaender, H., Gilbert, J., Hafsteinsson, H., and Kloks, T. 1995. Approximating treewidth, pathwidth, and minimum elimination tree height. J. Algor. 18, 238--255. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Bodlaender, H., Gustedt, J., and Telle, J. 1998. Linear-Time register allocation for a fixed number of registers and no stack variables. In Proceedings of the 9th ACM-SIAM Symposium on Discrete Algorithms, 574--583. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Bodlaender, H. and Kloks, T. 1996. Efficient and constructive algorithms for the pathwidth and treewidth of graphs. J. Algor. 21, 358--402. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Bodlaender, H. and Koster, A. 2006. Safe separators for treewidth. Discrete Math. 306, 337--350.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Bodlaender, H., Koster, A., and van den Eijkhof, F. 2005. Pre-Processing rules for triangulation of probabilistic networks. Comput. Intell. 21, 286--305.Google ScholarGoogle ScholarCross RefCross Ref
  30. Bodlaender, H., Koster, A., and Wolle, T. 2006. Contraction and treewidth lower bounds. J. Graph Algor. Appl. 10, 5--49.Google ScholarGoogle ScholarCross RefCross Ref
  31. Bodlaender, H. and Mohring, R. 1993. The pathwidth and treewidth of cographs. SIAM J. Discrete Math. 6, 181--186. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Borie, R. 1988. Recursively constructed graph families: Membership and linear algorithms. Ph.D. thesis, Georgia Institute of Technology. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Borie, R. 1995. Generation of polynomial-time algorithms for some optimization problems on tree-decomposable graphs. Algorithmica 14, 123--137.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Borie, R., Johnson, J., Raghavan, V., and Spinrad, J. 2002. Robust polynomial time algorithms on cliquewidth-k graphs. Manuscript.Google ScholarGoogle Scholar
  35. Borie, R., Parker, R., and Tovey, C. 1991a. Algorithms for recognition of regular properties and decomposition of recursive graph families. Annals Oper. Res. 33, 127--149.Google ScholarGoogle ScholarCross RefCross Ref
  36. Borie, R., Parker, R., and Tovey, C. 1991b. Deterministic decomposition of recursive graph classes. SIAM J. Discrete Math. 4, 481--501. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Borie, R., Parker, R., and Tovey, C. 1992. Automatic generation of linear-time algorithms from predicate calculus descriptions of problems on recursively constructed graph families. Algorithmica 7, 555--581.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Borie, R., Parker, R., and Tovey, C. 2004. Algorithms on recursively constructed graphs. In Handbook of Graph Theory, J. Gross and J. Yellen, eds. CRC Press, Chapter 10.4, 1046--1066.Google ScholarGoogle Scholar
  39. Bouchitté, V., Kratsch, D., Müller, H., and Todinca, I. 2004. On treewidth approximations. Discrete Appl. Math. 136, 183--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Brandstadt, A., Le, V., and Spinrad, J. 1999. Graph Classes: A Survey. SIAM Monographs on Discrete Mathematics and Applications. SIAM, Philadelphia, PA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Clautiaux, F., Carlier, J., Moukrim, A., and Negre, S. 2003. New lower and upper bounds for graph treewidth. In Proceedings of the 2nd International Workshop on Experimental and Efficient Algorithms. Lecture Notes in Computer Science, vol. 2647. Springer, 70--80.Google ScholarGoogle Scholar
  42. Clautiaux, F., Moukrim, A., Negre, S., and Carlier, J. 2004. Heuristic and meta-heuristic methods for computing graph treewidth. RAIRO Oper. Res. 38, 13--26.Google ScholarGoogle ScholarCross RefCross Ref
  43. Corneil, D., Habib, M., Lanlignel, J., Reed, B., and Rotics, U. 2000. Polynomial-Time recognition of clique-width ≤ 3 graphs. In Proceedings of the 4th Latin American Symposium on Theoretical Informatics. Lecture Notes in Computer Science, vol. 1776. Springer, 126--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Corneil, D. and Kirkpatrick, D. 1983. Families of recursively defined perfect graphs. Congressus Numer. 39, 237--246.Google ScholarGoogle Scholar
  45. Corneil, D., Lerchs, H., and Burlington, L. 1981. Complement reducible graphs. Discrete Appl. Math. 3, 163--174.Google ScholarGoogle ScholarCross RefCross Ref
  46. Corneil, D., Perl, Y., and Stewart, L. 1984. Cographs: Recognition, applications and algorithms. Congressus Numer. 43, 249--258.Google ScholarGoogle Scholar
  47. Corneil, D., Perl, Y., and Stewart, L. 1985. A linear recognition algorithm for cographs. SIAM Journal on Comput. 14, 926--934.Google ScholarGoogle ScholarCross RefCross Ref
  48. Corneil, D. and Rotics, U. 2005. On the relationship between clique-width and treewidth. SIAM J. Comput. 34, 825--847. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Cornuejols, G., Naddef, D., and Pulleyblank, W. 1983. Halin graphs and the travelling salesman problem. Math. Program. 26, 287--294.Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Courcelle, B. 1990. The monadic second-order logic of graphs I: Recognizable sets of finite graphs. Inf. Comput. 85, 12--75. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Courcelle, B. 1992. The monadic second-order logic of graphs III: Tree-Decompositions, minors, and complexity issues. Theor. Inf. Appl. 26, 257--286.Google ScholarGoogle ScholarCross RefCross Ref
  52. Courcelle, B. 1995. The monadic second-order logic of graphs VIII: Orientations. Annals Pure Appl. Logic 72, 103--143.Google ScholarGoogle ScholarCross RefCross Ref
  53. Courcelle, B. 1996. The monadic second-order logic of graphs X: Linear orderings. Theor. Comput. Sci. 160, 87--143. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Courcelle, B., Engelfriet, J., and Rozenberg, G. 1993. Handle-Rewriting hypergraph grammars. J. Comput. Syst. Sci. 46, 218--270. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Courcelle, B., Makowsky, J., and Rotics, U. 2000. Linear time solvable optimization problems on graphs of bounded clique width. Theory Comput. Syst. 33, 125--150.Google ScholarGoogle ScholarCross RefCross Ref
  56. Courcelle, B., Makowsky, J., and Rotics, U. 2001. On the fixed parameter complexity of graph enumeration problems definable in monadic second-order logic. Discrete Appl. Math. 108, 23--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Courcelle, B. and Mosbah, M. 1993. Monadic second-order evaluations on tree-decomposable graphs. Theor. Comput. Sci. 109, 49--82. Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Courcelle, B. and Olariu, S. 2000. Upper bounds to the clique-width of graphs. Discrete Appl. Math. 101, 77--114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. de Fluiter, B. 1997. Algorithms for graphs of small treewidth. Ph.D. thesis, University of Utrecht.Google ScholarGoogle Scholar
  60. Duffin, R. 1965. Topology of series-parallel networks. J. Math. Anal. Appl. 10, 303--318.Google ScholarGoogle ScholarCross RefCross Ref
  61. Edmonds, J. 1965a. Maximum matching and polyhedron of 0,1 vertices. J. Res. National Bureau Standards 69B, 125--130.Google ScholarGoogle ScholarCross RefCross Ref
  62. Edmonds, J. 1965b. Paths, trees, and flowers. Canadian J. Math. 17, 449--467.Google ScholarGoogle ScholarCross RefCross Ref
  63. Egervary, E. 1931. On combinatorial properties of matrices. Math. Phys. Pages 38, 16--28.Google ScholarGoogle Scholar
  64. El-Mallah, E. and Colbourn, C. 1988. Partial k-tree algorithms. Congressus Numer. 64, 105--119.Google ScholarGoogle Scholar
  65. Espelage, W., Gurski, F., and Wanke, E. 2001. How to solve NP-hard graph problems on clique-width bounded graphs in polynomial time. In Proceedings of the 27th International Workshop on Graph Theory. Lecture Notes in Computer Science, vol. 2204. Springer, 117--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Feige, U., Hajiaghayi, M., and Lee, J. 2005. Improved approximation algorithms for minimum-weight vertex separators. In Proceedings of the 37th ACM Symposium on Theory of Computing, 563--572. Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. Garey, M., Graham, R., Johnson, D., and Knuth, D. 1978. Complexity results for bandwidth minimization. SIAM J. Appl. Math. 34, 477--495.Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. Gavril, F. 1972. Algorithms for minimum coloring, maximum clique, minimum covering by cliques, and maximum independent set of a chordal graph. SIAM J. Comput. 1, 180--187.Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. Gogate, V. and Dechter, R. 2004. A complete anytime algorithm for treewidth. In Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence, 201--208. Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. Golumbic, M. and Rotics, U. 1999. On the clique-width of perfect graph classes. In Proceedings of the 25th International Workshop on Graph Theory. Lecture Notes in Computer Science, vol. 1665. Springer, 135--147. Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. Granot, D. and Skorin-Kapov, D. 1991. NC algorithms for recognizing partial 2-trees and 3-trees. SIAM J. Algebr. Discrete Methods 4, 342--354.Google ScholarGoogle ScholarCross RefCross Ref
  72. Gurski, F. and Wanke, E. 2000. The tree-width of clique-width bounded graphs without Kn,n. In Proceedings of the 26th International Workshop on Graph Theory. Lecture Notes in Computer Science, vol. 1928. Springer, 196--205. Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. Gurski, F. and Wanke, E. 2004. Vertex disjoint paths on clique-width bounded graphs. In Proceedings of the 6th Latin American Symposium on Theoretical Informatics. Lecture Notes in Computer Science, vol. 2976. Springer, 119--128.Google ScholarGoogle Scholar
  74. Gurski, F. and Wanke, E. 2006. Vertex disjoint paths on clique-width bounded graphs. Theor. Comput. Sci. 359, 188--199. Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Hare, E., Hedetniemi, S., Laskar, R., Peters, K., and Wimer, T. 1987. Linear-time computability of combinatorial problems on generalized series-parallel graphs. Discrete Algor. Complexity 14, 437--457.Google ScholarGoogle ScholarCross RefCross Ref
  76. He, X. and Yesha, Y. 1987. Parallel recognition and decomposition of two-terminal series-parallel graphs. Inf. Comput. 75, 15--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. Hicks, I., Koster, A., and Kolotoğlu, E. 2005. Branch and tree decomposition techniques for discrete optimization. In TutORials 2005, J. Smith, ed. Tutorials in Operations Research. INFORMS, New Orleans, LA, 1--29.Google ScholarGoogle Scholar
  78. Horton, S., Parker, R., and Borie, R. 1992. On some results pertaining to Halin graphs. Congressus Numer. 93, 65--86.Google ScholarGoogle Scholar
  79. Isobe, S., Zhou, X., and Nishizeki, T. 1999. A polynomial-time algorithm for finding total colorings of partial k-trees. Int. J. Foundat. Comput. Sci. 10, 171--194.Google ScholarGoogle ScholarCross RefCross Ref
  80. Ito, T., Nishizeki, T., and Zhou, X. 2003. Algorithms for multicolorings of partial k-trees. IEICE Trans. Inf. Syst. E86-D, 191--200.Google ScholarGoogle Scholar
  81. Jamison, B. and Olariu, S. 1995. Linear time optimization algorithms for P4-sparse graphs. Discrete Appl. Math. 61, 155--175. Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. Jensen, F., Lauritzen, S., and Olesen, K. 1990. Bayesian updating in recursive graphical models by local computation. Computat. Statist. Q. 4, 269--282.Google ScholarGoogle Scholar
  83. Johansson, O. 1998. Clique-Decomposition, NLC-decomposition, and modular decomposition relationships and results for random graphs. Congressus Numer. 132, 39--60.Google ScholarGoogle Scholar
  84. Johansson, O. 2000. NLC 2-decomposition in polynomial time. Int. J. Foundat. Comput. Sci. 11, 373--395.Google ScholarGoogle ScholarCross RefCross Ref
  85. Johnson, J. 2003. Polynomial time recognition and optimization algorithms on special classes of graphs. Ph.D. thesis, Vanderbilt University.Google ScholarGoogle Scholar
  86. Kajitani, Y., Ishizuka, A., and Ueno, S. 1985. A characterization of the partial k-tree in terms of certain structures. In Proceedings of the International Symposium on Circuits and Systems. IEEE, 1179--1182.Google ScholarGoogle Scholar
  87. Karp, R. 1972. Reducibility among combinatorial problems. In Complexity of Computer Computations. Plenum Press, New York, 85--103.Google ScholarGoogle Scholar
  88. Kashem, M., Zhou, X., and Nishizeki, T. 2000. Algorithms for generalized vertex-rankings of partial k-trees. Theoret. Comput. Sci. 240, 407--427. Google ScholarGoogle ScholarDigital LibraryDigital Library
  89. Kassios, I. 2001. Translating Borie-Parker-Tovey calculus into mutumorphisms. Manuscript.Google ScholarGoogle Scholar
  90. Klarlund, N. 1998. Mona and Fido: The logic-automaton connection in practice. In Computer Science Logic 1997. Lecture Notes in Computer Science, vol. 1414. Springer, 311--326. Google ScholarGoogle ScholarDigital LibraryDigital Library
  91. Klarlund, N., Moller, A., and Schwartzbach, M. 2002. Mona implementation secrets. Int. J. Foundat. Comput. Sci. 13, 571--586.Google ScholarGoogle ScholarCross RefCross Ref
  92. Kloks, T. 1994. Treewidth, Computations and Approximations. Lecture Notes in Computer Science, vol. 842. Springer.Google ScholarGoogle ScholarCross RefCross Ref
  93. Kloks, T. and Kratsch, D. 1995. Treewidth of chordal bipartite graphs. J. Algor. 19, 266--281. Google ScholarGoogle ScholarDigital LibraryDigital Library
  94. Kobler, D. and Rotics, U. 2003. Edge dominating set and colorings on graphs with fixed clique-width. Discrete Appl. Math. 126, 197--221. Google ScholarGoogle ScholarDigital LibraryDigital Library
  95. Koster, A. 1999. Frequency assignment—Models and algorithms. Ph.D. thesis, Maastricht University.Google ScholarGoogle Scholar
  96. Lauritzen, S. and Spiegelhalter, D. 1988. Local computations with probabilities on graphical structures and their application to expert systems. J. Royal Statist. Soc. Series B 50, 157--224.Google ScholarGoogle Scholar
  97. Lucena, B. 2003. A new lower bound for tree-width using maximum cardinality search. SIAM J. Discrete Math. 16, 345--353. Google ScholarGoogle ScholarDigital LibraryDigital Library
  98. Makowsky, J., Rotics, U., Averbouch, I., and Godlin, B. 2006. Computing graph polynomials on graphs of bounded clique-width. In Proceedings of the 32nd International Workshop on Graph Theory. Lecture Notes in Computer Science, vol. 4271. Springer, 191--204.Google ScholarGoogle Scholar
  99. Matousek, J. and Thomas, R. 1991. Algorithms for finding tree decompositions of graphs. J. Algor. 12, 1--22. Google ScholarGoogle ScholarDigital LibraryDigital Library
  100. Oum, S. 2005a. Approximating rank-width and clique-width quickly. In Proceedings of the 31st International Workshop on Graph Theory. Lecture Notes in Computer Science, vol. 3787. Springer, 49--58.Google ScholarGoogle Scholar
  101. Oum, S. 2005b. Graphs of bounded rank-width. Ph.D. thesis, Princeton University. Google ScholarGoogle ScholarDigital LibraryDigital Library
  102. Oum, S. and Seymour, P. 2006. Approximating clique-width and branch-width. J. Combinatorial Theory Series B 96, 514--528. Google ScholarGoogle ScholarDigital LibraryDigital Library
  103. Proskurowski, A. 1993. Graph reductions, and techniques for finding minimal forbidden minors. Graph Structure Theory 147, 591--600.Google ScholarGoogle ScholarCross RefCross Ref
  104. Rardin, R. and Parker, R. 1986. Subgraph isomorphism on partial 2-trees. Tech. Rep., Georgia Institute of Technology.Google ScholarGoogle Scholar
  105. Reed, B. 1992. Finding approximate separators and computing treewidth quickly. In Proceedings of the 24th Annual Symposium on Theory of Computing. ACM, 221--228. Google ScholarGoogle ScholarDigital LibraryDigital Library
  106. Reed, B. 1997. Treewidth and tangles: A new connectivity measure and some applications. In Surveys in Combinatorics. London Mathematical Society Lecture Note Series, vol. 241. Cambridge University Press, London, 87--162. Invited papers from 16th British Combinatorial Conference.Google ScholarGoogle Scholar
  107. Richey, M. 1985. Combinatorial optimization on series-parallel graphs: Algorithms and complexity. Ph.D. thesis, Georgia Institute of Technology. Google ScholarGoogle ScholarDigital LibraryDigital Library
  108. Robertson, N. and Seymour, P. 1983. Graph minors I: Excluding a forest. J. Combinatorial Theory Series B 35, 39--61.Google ScholarGoogle ScholarCross RefCross Ref
  109. Robertson, N. and Seymour, P. 1984. Graph minors III: Planar treewidth. J. Combinatorial Theory Series B 36, 49--64.Google ScholarGoogle ScholarCross RefCross Ref
  110. Robertson, N. and Seymour, P. 1986a. Graph minors II: Algorithmic aspects of treewidth. J. Algor. 7, 309--322.Google ScholarGoogle ScholarCross RefCross Ref
  111. Robertson, N. and Seymour, P. 1986b. Graph minors V: Excluding a planar graph. J. Combinatorial Theory Series B 41, 92--114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  112. Robertson, N. and Seymour, P. 1986c. Graph minors VI: Disjoint paths across a disc. J. Combinatorial Theory Series B 41, 115--138. Google ScholarGoogle ScholarDigital LibraryDigital Library
  113. Robertson, N. and Seymour, P. 1988. Graph minors VII: Disjoint paths on a surface. J. Combinatorial Theory Series B 45, 212--254. Google ScholarGoogle ScholarDigital LibraryDigital Library
  114. Robertson, N. and Seymour, P. 1990a. Graph minors IV: Treewidth and well-quasi-ordering. J. Combinatorial Theory Series B 48, 227--254. Google ScholarGoogle ScholarDigital LibraryDigital Library
  115. Robertson, N. and Seymour, P. 1990b. Graph minors IX: Disjoint crossed paths. J. Combinatorial Theory Series B 49, 40--77. Google ScholarGoogle ScholarDigital LibraryDigital Library
  116. Robertson, N. and Seymour, P. 1990c. Graph minors VIII: A Kuratowski theorem for general surfaces. J. Combinatorial Theory Series B 48, 255--288. Google ScholarGoogle ScholarDigital LibraryDigital Library
  117. Robertson, N. and Seymour, P. 1991. Graph minors X: Obstructions to tree decompositions. J. Combinatorial Theory Series B 52, 153--190. Google ScholarGoogle ScholarDigital LibraryDigital Library
  118. Robertson, N. and Seymour, P. 1992. Graph minors XXII: Irrelevant vertices in linkage problems. Manuscript.Google ScholarGoogle Scholar
  119. Robertson, N. and Seymour, P. 1994. Graph minors XI: Distance on a surface. J. Combinatorial Theory Series B 60, 72--106. Google ScholarGoogle ScholarDigital LibraryDigital Library
  120. Robertson, N. and Seymour, P. 1995. Graph minors XIII: The disjoint paths problem. J. Combinatorial Theory Series B 63, 65--110. Google ScholarGoogle ScholarDigital LibraryDigital Library
  121. Robertson, N. and Seymour, P. 2003. Graph minors XVI: Excluding a non-planar graph. J. Combinatorial Theory Series B 89, 43--76. Google ScholarGoogle ScholarDigital LibraryDigital Library
  122. Robertson, N. and Seymour, P. 2004. Graph minors XX: Wagner's conjecture. J. Combinatorial Theory Series B 92, 325--357. Google ScholarGoogle ScholarDigital LibraryDigital Library
  123. Robertson, N., Seymour, P., and Thomas, R. 1994. Quickly excluding a planar graph. J. Combinatorial Theory Series B 62, 323--348. Google ScholarGoogle ScholarDigital LibraryDigital Library
  124. Rose, D. 1974. On simple characterization of k-trees. Discrete Math. 7, 317--322.Google ScholarGoogle ScholarDigital LibraryDigital Library
  125. Sanders, D. 1993. Linear algorithms for graphs of tree-width at most four. Ph.D. thesis, Georgia Institute of Technology. Google ScholarGoogle ScholarDigital LibraryDigital Library
  126. Sanders, D. 1996. On linear recognition of tree-width at most four. SIAM J. Discrete Mathematics 9, 101--117. Google ScholarGoogle ScholarDigital LibraryDigital Library
  127. Sasano, I., Hu, Z., Takeichi, M., and Ogawa, M. 2000. Make it practical: A generic linear-time algorithm for solving maximum-weightsum problems. ACM SIGPLAN Not. 35, 137--149. Google ScholarGoogle ScholarDigital LibraryDigital Library
  128. Satyanarayana, A. and Tung, L. 1990. A characterization of partial 3-trees. Netw. 20, 299--322.Google ScholarGoogle ScholarCross RefCross Ref
  129. Scheffler, P. 1987. Linear-Time algorithms for NP-complete problems restricted to partial k-trees. Tech. Rep. R-MATH-03/87, Akademie der Wissenschaften der DDR.Google ScholarGoogle Scholar
  130. Scheffler, P. 1988. What graphs have bounded treewidth? In Fischland Colloquium on Discrete Mathematics and Applications.Google ScholarGoogle Scholar
  131. Scheffler, P. 1989. The treewidth of graphs as a measure for the complexity of algorithmic problems. Ph.D. thesis, German Academy of Sciences Berlin.Google ScholarGoogle Scholar
  132. Scheffler, P. and Seese, D. 1986. Graphs of bounded tree-width and linear-time algorithms for NP-complete problems. In Bilateral Seminar.Google ScholarGoogle Scholar
  133. Scheffler, P. and Seese, D. 1988. A combinatorial and logical approach to linear-time computability. In Proceedings of the European Conference on Computer Algebra. Lecture Notes in Computer Science, vol. 378. Springer, 379--380. Google ScholarGoogle ScholarDigital LibraryDigital Library
  134. Seymour, P. and Thomas, R. 1993. Graph searching and a min-max theorem for treewidth. J. Combinatorial Theory Series B 58, 22--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  135. Seymour, P. and Thomas, R. 1994. Call routing and the ratcatcher. Combinatorica 14, 217--241.Google ScholarGoogle ScholarCross RefCross Ref
  136. Spinrad, J. 2003. Efficient Graph Representations. Fields Institute Monographs. AMS, Brooklyn, NY.Google ScholarGoogle Scholar
  137. Syslo, M. 1983. NP-Complete problems on some tree-structured graphs: A review. In Proceedings of the 9th Workshop on Graph-Theoretic Concepts in Computer Science, 342--353.Google ScholarGoogle Scholar
  138. Takamizawa, K., Nishizeki, T., and Saito, N. 1982. Linear-Time computability of combinatorial problems on series-parallel graphs. J. ACM 29, 623--641. Google ScholarGoogle ScholarDigital LibraryDigital Library
  139. Telle, J. and Proskurowski, A. 1993. Efficient sets in partial k-trees. Discrete Appl. Math. 44, 109--117. Google ScholarGoogle ScholarDigital LibraryDigital Library
  140. Telle, J. and Proskurowski, A. 1997. Algorithms for vertex partitioning problems on partial k-trees. SIAM J. Discrete Math. 10, 529--550. Google ScholarGoogle ScholarDigital LibraryDigital Library
  141. Thorup, M. 1998. All structured programs have small tree-width and good register allocation. Inf. Comput. 142, 159--181. Google ScholarGoogle ScholarDigital LibraryDigital Library
  142. Valdes, J., Tarjan, R., and Lawler, E. 1982. The recognition of series parallel digraphs. SIAM J. Comput. 11, 298--313.Google ScholarGoogle ScholarDigital LibraryDigital Library
  143. Vizing, V. 1964. On an estimate of the chromatic class of a p-graph. Discrete Anal. 3, 25--30.Google ScholarGoogle Scholar
  144. Wanke, E. 1994. k-NLC graphs and polynomial algorithms. Discrete Appl. Math. 54, 251--266. Later revised with new co-author F. Gurski. Google ScholarGoogle ScholarDigital LibraryDigital Library
  145. Wimer, T. 1987. Linear algorithms on k-terminal recursive graphs. Ph.D. thesis, Clemson University. Google ScholarGoogle ScholarDigital LibraryDigital Library
  146. Wimer, T. and Hedetniemi, S. 1988. K-terminal recursive families of graphs. Congressus Numer. 63, 161--176.Google ScholarGoogle Scholar
  147. Wimer, T., Hedetniemi, S., and Laskar, R. 1985. A methodology for constructing linear graph algorithms. Congressus Numer. 50, 43--60.Google ScholarGoogle Scholar
  148. Zhou, X., Fuse, K., and Nishizeki, T. 2000. A linear algorithm for finding {g,f}-colorings of partial k-trees. Algorithmica 27, 227--243.Google ScholarGoogle ScholarCross RefCross Ref
  149. Zhou, X., Kanari, Y., and Nishizeki, T. 2000. Generalized vertex-colorings of partial k-trees. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. E83-A, 671--678.Google ScholarGoogle Scholar
  150. Zhou, X., Nakano, S., and Nishizeki, T. 1993. A linear algorithm for edge-coloring partial k-trees. In Proceedings of the 1st Annual European Symposium on Algorithms. Lecture Notes in Computer Science, vol. 726. Springer, 409--418. Google ScholarGoogle ScholarDigital LibraryDigital Library
  151. Zhou, X., Nakano, S., and Nishizeki, T. 1996. Edge-Coloring partial k-trees. J. Algor. 21, 598--617. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Solving problems on recursively constructed graphs

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Computing Surveys
        ACM Computing Surveys  Volume 41, Issue 1
        January 2009
        281 pages
        ISSN:0360-0300
        EISSN:1557-7341
        DOI:10.1145/1456650
        Issue’s Table of Contents

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 15 January 2009
        • Accepted: 1 January 2008
        • Revised: 1 October 2007
        • Received: 1 July 2007
        Published in csur Volume 41, Issue 1

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader