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Solving the degree-concentrated fault-tolerant spanning subgraph problem by DC programming

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Abstract

In this paper, we consider the maximum and minimum versions of degree-concentrated fault-tolerant spanning subgraph problem which has many applications in network communications. We prove that both this two problems are NP-hard. For the maximum version, we use DC programming relaxation to propose a heuristic algorithm. Numerical tests indicate that the proposed algorithm is efficient and effective. For the minimum version, we also formulate it as a DC program, and show that the DC algorithm does not perform well for this problem.

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References

  1. Bondy, J.A., Murty, U.S.R.: Graph Theory. Springer, New York (2008)

    Book  MATH  Google Scholar 

  2. Boros, E., Borys, K., Elbassioni, K., Gurvich, V., Makino, K., Rudolf, G.: Generating minimal \(k\)-vertex connected spanning subgraphs. In: Proceedings of the 13th International Computing and Combinatorics Conference, pp. 222–231 (2007)

  3. Byrka, J., Grandoni, F., Rothvoss, T., Sanitá, L.: Steiner tree approximation via iterative randomized rounding. J. ACM 60(1), 6 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  4. Chakraborty, T., Chuzhoy, J., Khanna, S.: Network design for vertex connectivity. In: Proceedings of the 40th Annual ACM Symposium on Theory of Computing, pp. 167–176 (2008)

  5. Cornaz, D., Magnouche, Y.: On minimal two-edge-connected graphs. In: Proceedings of 2014 International Conference on Control, Decision and Information Technologies, pp. 251–256 (2014)

  6. Coulbourn, C.J.: The Combinatorics of Network Reliability. Oxford University Press, Oxford (1987)

    Google Scholar 

  7. Dinh, T.N., Xuan, Y., Thai, M.T., Pardalos, P.M., Znati, T.: On new approaches of assessing network vulnerability: hardness and approximation. IEEE ACM Trans. Netw. 20, 609–619 (2011)

    Article  Google Scholar 

  8. Frank, A.: Increasing the rooted-connectivity of a digraph by one. Math. Program. Ser. B 84, 565–576 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  9. Garey, M.R., Johnson, D.S.: Computers and Intractability—A Guide to the Theory of NP-Completeness. Freeman, San Francisco (1979)

    MATH  Google Scholar 

  10. Goemans, M.X., Williamson, D.P.: Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM 42, 1115–1145 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  11. Khuller, S.: Approximation algorithms for finding highly connected subgraphs. In: Hochbaum, D.S. (ed.) Approximation Algorithms for NP-Hard Problems, pp. 236–265. PWS Publishing Company, Boston, MA (1997)

    Google Scholar 

  12. Kobayashi, Y.: The complexity of maximizing the difference of two matorid rank functions. METR2014-42, University of Tokyo (2014)

  13. Kortsarz, G., Nutov, Z.: Chapter 58: Approximating minimum cost connectivity problems. In: Gonzalez, T.F. (ed.) Handbook on Approximation Algorithms and Metaheuristics. Chapman Hall, Santa Barbara (2007)

    Google Scholar 

  14. Le Thi, H.A.: An efficient algorithm for globally minimizing a quadratic function under convex quadratic constraints. Math. Program. Ser. A 87, 401–426 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  15. Le Thi, H.A., Pham Dinh, T.: Solving a class of linearly constrained indefinite quadratic problems by D.C. algorithms. J. Glob. Optim. 11, 253–285 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  16. Le Thi, H.A., Pham Dinh, T.: The DC (difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems. Ann. Oper. Res. 133, 23–46 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  17. Le Thi, H.A., Pham Dinh, T., Yen, N.D.: Properties of two DC algorithms in quadratic programming. J. Glob. Optim. 49, 481–495 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  18. Le Thi, H.A., Pham Dinh, T., Ngai, H.V.: Exact penalty and error bounds in DC programming. J. Glob. Optim. 52, 509–535 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  19. Lenstra, J.K., Shmoys, D.B., Tardos, E.: Approximation algorithms for scheduling unrelated parallel machines. Math. Program. 46, 259–271 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  20. Li, S.: A 1.488 approximation algorithm for the uncapacitated facility location problem. Inf. Comput. 222, 45–58 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  21. Maehara, T., Marumo, N., Murota, K.: Continuous relaxation for discrete DC programming. In: Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, pp. 181–190 (2015)

  22. Maehara, T., Murota, K.: A framework of discrete DC programming by discrete convex analysis. Math. Program. Ser. A 152, 435–466 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  23. Murota, K.: Discrete Convex Analysis. Society for Industrial and Applied Mathematics, Philadelphia (2003)

    Book  MATH  Google Scholar 

  24. Pham Dinh, T., Souad, E.B.: Algorithms for solving a class of nonconvex optimization problems: methods of subgradients. In: Hiriart-Urruty, J.B. (ed.) Fermat Days 85: Mathematics for Optimization, North-Holland Mathematics Studies, vol. 129, pp. 249–271. North-Holland, Amsterdam (1986)

    Chapter  Google Scholar 

  25. Pham Dinh, T., Canh, N.N., Le Thi, H.A.: An efficient combined DCA and B&B using DC/SDP relaxation for globally solving binary quadratic programs. J. Glob. Optim. 48, 595–632 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  26. Strekalovsky, A.S.: On local search in D.C. optimization problems. Appl. Math. Comput. 255, 73–83 (2015)

    MathSciNet  MATH  Google Scholar 

  27. Tanenbaum, A.S.: Computer Networks, 5th edn. Prentice Hall, Upper Saddle River (2010)

    MATH  Google Scholar 

  28. Tao, P.D., An, L.T.E.: Convex analysis approach to D.C. programming: theory, algorithm and applications. Acta Math. Vietnam. 22(1), 289–355 (1997)

    MathSciNet  Google Scholar 

  29. Tarjan, R.: Depth-first search and linear graph algorithms. SIAM J. Comput. 1, 146–160 (1972)

    Article  MathSciNet  MATH  Google Scholar 

  30. Williamson, D.P., Shmoys, D.B.: The Design of Approximation Algorithms. Cambridge University Press, Cambridge (2011)

    Book  MATH  Google Scholar 

  31. Xu, J.M.: Combinatorial Theory in Networks. Academic Press, Cambridge (2013)

    Google Scholar 

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Acknowledgements

The first author was partially supported by NSFC (No. 11501412). The fourth author was partially supported by the Paul and Heidi Brown Preeminent Professorship at ISE, University of Florida. The fifth author was partially supported by NSFC (No. 11531014). The sixth author was partially supported by NSFC (Nos. 61222201 and 11531011).

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Correspondence to Dachuan Xu.

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Wu, C., Wang, Y., Lu, Z. et al. Solving the degree-concentrated fault-tolerant spanning subgraph problem by DC programming. Math. Program. 169, 255–275 (2018). https://doi.org/10.1007/s10107-018-1242-z

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  • DOI: https://doi.org/10.1007/s10107-018-1242-z

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