Abstract
The approximate range computation problem is one of the basic problem of interval computations. It is well known that this problem and even some special cases of it are at least as hard as any \(\mathbf {NP}\)-problem. First, we show that the general approximate range computation problem is not harder than \(\mathbf {NP}\)-problems. Then we show that the computional complexity of some further variants of this problem is closely related to some well-known open questions from structural complexity theory that seem to be slightly weaker than the famous open question whether the complexity class \(\mathbf {NP}\) is equal to the complexity class \(\mathbf {P}\), namely to the question whether \(\mathbf {NE}\) is equal to \(\mathbf {E}\), to the question whether \(\mathbf {NEXP}\) is equal to \(\mathbf {EXP}\) and, finally, to the question whether every \(\mathbf {NP}\)-real number is polynomial time computable.
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References
S. Ferson, L. Ginzburg, V. Kreinovich, L. Longpré, M. Aviles, Computing variance for interval data is NP-hard. SIGACT News 33(2), 108–118 (2002)
A. Gaganov, Computation Complexity of the Range of a Polynomial in Several Variables. Leningrad University, Math. Department. M.S. Thesis (1981)
A. Gaganov, Computation complexity of the range of a polynomial in several variables. Cybernetics 21, 418–421 (1985)
D. Grigor’ev, N. Vorobjov, Solving systems of polynomial inequalities in subexponential time. J. Symb. Comput. 5(1–2), 37–64 (1988)
A. Kawamura, S. Cook, Complexity theory for operators in analysis. ACM Trans. Comput. Theory 4(2), 24 (2012)
K.-I. Ko, The maximum value problem and NP real numbers. J. Comput. Syst. Sci. 24, 15–35 (1982)
K.-I. Ko, Complexity Theory of Real Functions, (Progress in Theoretical Computer Science. Birkhäuser, Boston, 1991)
V. Kreinovich, A. Lakeyev, J. Rohn, P. Kahl, Computational Complexity and Feasibility of Data Processing and Interval Computations. (Kluwer Academic Publishers, Dordrecht, 1998)
H.T. Nguyen, V. Kreinovich, B. Wu, G. Xiang, Computing Statistics Under interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering. (Springer, Berlin, 2012)
C.H. Papadimitriou, Computational Complexity, (Addison-Wesley Publishing Company, Amsterdam, 1994)
S. Sahni, Computationally related problems. SIAM J. Comput. 3(4), 262–279 (1974)
S.A. Vavasis, Nonlinear Optimization: Complexity Issues. (Oxford University Press, New York, 1991)
Acknowledgements
This article is dedicated to Professor Vladik Kreinovich on the occasion of his 65th birthday.
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Hertling, P. (2020). On the Computational Complexity of the Range Computation Problem. In: Kosheleva, O., Shary, S., Xiang, G., Zapatrin, R. (eds) Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their Applications. Studies in Computational Intelligence, vol 835. Springer, Cham. https://doi.org/10.1007/978-3-030-31041-7_15
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DOI: https://doi.org/10.1007/978-3-030-31041-7_15
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