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Polynomial Time Approximation Schemes and Parameterized Complexity

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Mathematical Foundations of Computer Science 2004 (MFCS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3153))

Abstract

In this paper, we study the relationship between the approximability and the parameterized complexity of NP optimization problems. We introduce the notion of efficient fixed-parameter tractability and prove that, under a very general constraint, an NP optimization problem has a fully polynomial time approximation scheme if and only if the problem is efficiently fixed-parameter tractable. By enforcing a constraint of planarity on the W-hierarchy studied in parameterized complexity theory, we obtain a class of NP optimization problems, the planar W -hierarchy, and prove that all problems in this class have efficient polynomial time approximation schemes (EPTAS).

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References

  1. Alber, J., Bodlaender, H., Fernau, H., Kloks, T., Niedermeier, R.: Fixed parameter algorithms for dominating set and related problems on planar graphs. Algorithmica 33, 461–493 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  2. Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti- Spaccamela, A., Protasi, M.: Complexity and Approximation, Combinatorial optimization problems and their approximability properties. Springer, Heidelberg (1999)

    MATH  Google Scholar 

  3. Ausiello, G., Marchetti-spaccamela, A., Protasi, M.: Toward a unified approach for the classification of NP-complete optimization problems. Theoretical Computer Science 12, 83–96 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  4. Arora, S.: Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems. J. ACM 45, 753–782 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  5. Baker, B.: Approximation algorithms for NP-complete problems on planar graphs. J. ACM 41, 153–180 (1994)

    Article  MATH  Google Scholar 

  6. Cai, L., Chen, J.: On fixed-parameter tractability and approximability of NP optimization problems. Journal of Computer and System Sciences 54, 465–474 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  7. Cai, L., Fellows, M., Juedes, D., Rosamond, F.: On efficient polynomialtime approximation schemes for problems on planar structures. Journal of Computer and System Sciences (to appear)

    Google Scholar 

  8. Cesati, M., Trevisan, L.: On the efficiency of polynomial time approximation schemes. Information Processing Letters 64, 165–171 (1997)

    Article  MathSciNet  Google Scholar 

  9. Chen, J.: Characterizing parallel hierarchies by reducibilities. Information Processing Letters 39, 303–307 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  10. Chen, J., Miranda, A.: A polynomial time approximation scheme for general multiprocessor job scheduling. SIAM J. on Comp. 31, 1–17 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  11. Downey, R.: Parameterized complexity for the skeptic. In: Proc. 18th IEEE Annual Conference on Computational Complexity (CCC 2003), pp. 132–153 (2003)

    Google Scholar 

  12. Downey, R., Fellows, M.: Parameterized Complexity. Springer, Heidelberg (1999)

    Google Scholar 

  13. Fellows, M.R.: Parameterized complexity: The main ideas and some research frontiers. In: Eades, P., Takaoka, T. (eds.) ISAAC 2001. LNCS, vol. 2223, pp. 291–307. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  14. Frick, M., Grohe, M.: Deciding first-order properties of locally treedecomposable structures. J. ACM 48, 1184–1206 (2001)

    Article  MathSciNet  Google Scholar 

  15. Garey, M., Johnson, D.: Computers and Intractability: A Guide to the Theory of NP-Completeness. H. Freeman, New York (1979)

    MATH  Google Scholar 

  16. Hochbaum, D.: Approximation Algorithms for NP-hard Problems. PWS Publishing Company, Boston (1997)

    Google Scholar 

  17. Ibarra, O., Kim, C.: Fast approximation algorithms for the knapsack and sum of subset problems. J. ACM 22, 463–468 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  18. Khanna, S., Motwani, R.: Towards a syntactic characterization of PTAS. In: Proc. 28th Annual ACM Symp. on Theory of Computing (STOC 1996), pp. 468–477 (1996)

    Google Scholar 

  19. Khanna, S., Motwani, R., Sudan, M., Vazirani, U.: On syntactic versus computational views of approximability. SIAM J. on Comp. 28, 164–191 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  20. Paz, A., Moran, S.: Non deterministic polynomial optimization problems and their approximations. Theoretical Computer Science 15, 251–277 (1981)

    Article  MATH  MathSciNet  Google Scholar 

  21. Papadimitriou, C., Yannakakis, M.: Optimization, approximation, and complexity classes. Journal of Computer and System Sciences 43, 425–440 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  22. Sahni, S.: Algorithms for scheduling independent tasks. J. ACM 23, 116–127 (1976)

    Article  MATH  MathSciNet  Google Scholar 

  23. Woeginger, G.: When does a dynamic programming formulation guarantee the existence of an FPTAS? In: Proc. 10th Annual ACM-SIAM Symp. on Discrete Algorithms (SODA 1999), pp. 820–829 (1999)

    Google Scholar 

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Chen, J., Huang, X., Kanj, I.A., Xia, G. (2004). Polynomial Time Approximation Schemes and Parameterized Complexity. In: Fiala, J., Koubek, V., Kratochvíl, J. (eds) Mathematical Foundations of Computer Science 2004. MFCS 2004. Lecture Notes in Computer Science, vol 3153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28629-5_38

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  • DOI: https://doi.org/10.1007/978-3-540-28629-5_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22823-3

  • Online ISBN: 978-3-540-28629-5

  • eBook Packages: Springer Book Archive

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