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Shortest Path Algorithms for the Approximation by Nomographic Functions

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Anniversary Volume on Approximation Theory and Functional Analysis

Abstract

Continuous functions of two real variables are approximated on compact domains in the uniform norm by the classes NOM of nomographic functions which appear as approximation subspaces in bivariate approximation theory, in the theory of integral equations., functional equations, scalings of matrices, Goursat-type problems for the wave equation. The approximation problem is converted into the negative cycle problem in a properly chosen family of weighted directed graphs, and a version of the Ford-Bellman algorithm for finding the shortest paths leads to constructive proofs of new characterization and existence theorems.

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References

  1. Aumann, G. Ober approximative Nomographic II. Bayer. Akad. Wiss. Math. Nat. Kl. S. B., (1959), 103–109.

    Google Scholar 

  2. Buck, R.C. On approximation theory and functional equations. J. Approximation Theory 5 (1972), 228–237.

    Article  Google Scholar 

  3. Cheney, E.W. Approximating multivariate functions by combinations of univariate ones. Center for Numerical Analysis, The University of Texas, Report 148 (1979).

    Google Scholar 

  4. Cheney, E.W. — v. Golitschek, M. On the algorithm of Di liberto and Straus for approximating bivariate functions by univariate ones. Numer. Funet. Anal, and Optimiz. 1 (1979), 341–363.

    Article  Google Scholar 

  5. Cheney, E.W. — Light, W.A. On the approximation of a bivariate function by the sum of univariat ones. J. Approximation Theory, to appear.

    Google Scholar 

  6. Collatz, L. Approximation by functions of fewer variables. In: Lecture Notes in Mathematics 280 (1972), 16–31.

    Article  Google Scholar 

  7. Dantzig, G.B. — Blattner, W.O. — Rao, M.R. Finding a cycle in a graph with minimum cost to time ratio with applications to a ship routing problem. In: Theory of Graphs (P. Rosenstiehl, ed.), International Symposium, Rome 1966, pp. 77–83.

    Google Scholar 

  8. Diliberto, S.P. — Straus, E.G. On the approximation of functions of several variables by the sum of functions of fewer variables. Pacific J. Math. 1 (1951), 195–210.

    Article  Google Scholar 

  9. Fox, B. Finding minimum cost-time ratio curcuits. Operations Research 17 (1969), 546–551.

    Article  Google Scholar 

  10. Fulkerson, D.R. — Wolfe, P. An algorithm for scaling matrices. SIAM Rev. 4 (1962), 142–146.

    Article  Google Scholar 

  11. v. Golitschek, M. Approximation of functions of two variables by the sum of two functions of one variable. In: Numerical Methods of Approximation Theory (L. Collatz, G. Meinardus, H. Werner, eds.), Birkhäuser Verlag, ISNM 52 (1980), pp. 117–124.

    Google Scholar 

  12. v. Golitschek, M. An algorithm for scaling matrices and computing the minimum cycle mean in a digraph. Numer. Math. 35 (1980), 45–55.

    Article  Google Scholar 

  13. v. Golitschek, M. Optimal cycles in doubly weighted graphs and approximation of bivariate functions by univariate ones. Numer. Math. 39 (1982), 65–84.

    Article  Google Scholar 

  14. v. Golitschek, M. Approximating bivariate functions and matrices by nomographic functions. In: Quantitative Approximation (R. DeVore, K. Scherer, eds,), Academic Press, New York 1980, pp.143–151.

    Google Scholar 

  15. v.Golitschek, M. — Rothblum, U.G. — Schneider, H. A conforming decomposition theorem, a piecewise linear theorem of the alternative, and scalings of matrices satisfying lower and upper bounds. Mathematical Programming, to appear.

    Google Scholar 

  16. v. Golitschek, M. — Schneider, H. Applications of shortest path algorithms to matrix scalings. Numer, Math., to appear.

    Google Scholar 

  17. Golomb, M. Approximation by functions of fewer variables.In: Numerical Approximation (R. Langer, ed.), Madison 1959, pp.275–327.

    Google Scholar 

  18. Havinson, S.J. A Chebyshev theorem for the approximation of a function of two variables by the sum Φ(x) + Ψ(y). Izv. Akad. Nauk SSSR Ser. Mat. 33. (1969), 650–666.

    Google Scholar 

  19. Holmes, R.B. Geometrical Functional Analysis and its Applications, Springer Verlag, New York 1975.

    Book  Google Scholar 

  20. Karp, R.M, A characterization of the minimum cycle mean in a digraph. Discrete Math. 23 (1978), 309–311.

    Google Scholar 

  21. Lawler, E.L. Optimal cycles in doubly weighted directed linear graphs. In: Theory of Graphs (P. Rosenstiehl, ed.), International Symposium, Rome 1966, pp.209–213.

    Google Scholar 

  22. Lawler, E.L. Optimal cycles in graphs and the minimal cost-to-time ratio problem. In: Periodic Optimization, Vol. I (A. Marzollo, ed.) Udine 1972, pp.37–60.

    Google Scholar 

  23. Lawler, E.L. Combinatorial Optimization: Networks and Matroids. New York 1976.

    Google Scholar 

  24. Michael, E. Continuous selections. Ann. Math. 63 (1956), 361–382.

    Article  Google Scholar 

  25. Ofman, J.P. Best approximation of functions of two variables by functions of the form Φ(x) + Ψ(y). Amer. Math. Soc. Transl. 44 (1965), 12–29.

    Google Scholar 

  26. Rothblum, U.G. — Schneider, H. Characterizations of optimal scalings of matrices. Mathematical Programming 19 (1980), 121–136.

    Article  Google Scholar 

  27. Saunders, B.D. — Schneider, H. Flows on graphs applied to diagonal similarity and diagonal equivalence of matrices. Discrete Mathematics 24 (1978), 202–220.

    Google Scholar 

  28. Yen, J.Y. Shortest Path Network Problems. Mathematical Systems in Economics 18, Meisenheim 1975.

    Google Scholar 

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© 1984 Springer Basel AG

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Golitschek, M.v. (1984). Shortest Path Algorithms for the Approximation by Nomographic Functions. In: Butzer, P.L., Stens, R.L., Sz.-Nagy, B. (eds) Anniversary Volume on Approximation Theory and Functional Analysis. ISNM 65: International Series of Numerical Mathematics / Internationale Schriftenreihe zur Numerischen Mathematik / Série internationale d’Analyse numérique, vol 65. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-5432-0_27

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  • DOI: https://doi.org/10.1007/978-3-0348-5432-0_27

  • Publisher Name: Birkhäuser, Basel

  • Print ISBN: 978-3-0348-5434-4

  • Online ISBN: 978-3-0348-5432-0

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