Verification methods for conic linear programming problems

Author:

Lange Marko1ORCID

Affiliation:

1. Institute of Reliable Computing, Hamburg University of Technology Am Schwarzenberg-Campus 3

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Reference65 articles.

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2. [2] R.B. Kearfott, M.T. Nakao, A. Neumaier, S.M. Rump, S.P. Shary, and P. van Hentenryck, “Standardized notation in interval analysis,” Comput. Technol., vol. 15, no. 1, pp. 7-13, 2010.

3. [3] S.M. Rump, “Verification methods: Rigorous results using floating-point arithmetic,” Acta Numer., vol. 19, pp. 287-449, 2010.

4. [4] S. Oishi, K. Ichihara, M. Kashiwagi, T. Kimura, X. Liu, H. Masai, Y. Morikura, T. Ogita, K. Ozaki, S.M. Rump, K. Sekine, A. Takayasu, and N. Yamanaka, Principle of Verified Numerical Computations, Tokyo, Japan: Corona publisher, 2018.[in Japanese].

5. [5] R. Krawczyk, “Fehlerabschätzung bei linearer Optimierung,” Interval Mathematics (K. Nickel, ed.), pp. 215-222, Springer Berlin Heidelberg, 1975.

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1. Interval Linear Programming: Optimal Value Range;Encyclopedia of Optimization;2022-09-30

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