Modified Piyavskii’s Global One-Dimensional Optimization of a Differentiable Function

Abstract

Piyavskii’s algorithm maximizes a univariate function satisfying a Lipschitz condition. We propose a modified Piyavskii’s sequential algorithm which maximizes a univariate differentiable function f by iteratively constructing an upper bounding piece-wise concave function Φ of f and evaluating f at a point where Φ reaches its maximum. We compare the numbers of iterations needed by the modified Piyavskii’s algorithm (*n*_{C}) to obtain a bounding piece-wise concave function Φ whose maximum is within ε of the globally optimal value *f*_{opt}with that required by the reference sequential algorithm (*n*_{ref}). The main result is that *n*_{C}≤ 2*n*_{ref} + 1 and this bound is sharp. We also show that the number of iterations needed by modified Piyavskii’s algorithm to obtain a globally ε-optimal value together with a corresponding point (*n*_{B}) satisfies *n*_{B}n_{ref} + 1 Lower and upper bounds for *n*_{ref} are obtained as functions of *f*(*x*) , ε, M1 and M0 where M0 is a constant defined by *M*_{0} = sup_{x∈[a,b]} - *f’’*(*x*) and *M*_{1} ≥ *M*_{0} is an evaluation of *M*_{0}.

Piyavskii’s algorithm maximizes a univariate function satisfying a Lipschitz condition. We propose a modified Piyavskii’s sequential algorithm which maximizes a univariate differentiable function f by iteratively constructing an upper bounding piece-wise concave function Φ of f and evaluating f at a point where Φ reaches its maximum. We compare the numbers of iterations needed by the modified Piyavskii’s algorithm (

Cite this paper

R. Ellaia, M. Es-Sadek and H. Kasbioui, "Modified Piyavskii’s Global One-Dimensional Optimization of a Differentiable Function,"*Applied Mathematics*, Vol. 3 No. 10, 2012, pp. 1306-1320. doi: 10.4236/am.2012.330187.

R. Ellaia, M. Es-Sadek and H. Kasbioui, "Modified Piyavskii’s Global One-Dimensional Optimization of a Differentiable Function,"

References

[1] R. Horst and H. Tuy, “Global Optimization-Deterministic Approaches,” 2nd Edition, Springer, Berlin, 1992.

[2] S. A. Piyavskii, “An Algorithm for Finding the Absolute Minimum of a Function,” USSR Computational Mathematics and Mathematical Physics, Vol. 12, No. 4, 1967, pp. 13-24.

[3] S. A. Piyavskii, “An Algorithm for Finding the Absolute Minimum of a Function,” USSR Computational Mathematics and Mathematical Physics, Vol. 12, No. 4, 1967, pp. 57-67. doi:10.1016/0041-5553(72)90115-2

[4] B. O. Shubert, “A Sequential Method Seeking the Global Maximum of a Function,” SIAM Journal on Numerical Analysis, Vol. 9, No. 3, 1972, pp. 379-388.
doi:10.1137/0709036

[5] P. Basso, “Iterative Method for the Localization of the Global Maximum,” SIAM Journal on Numerical Analysis, Vol. 19, No. 4, 1982, pp. 781-792. doi:10.1137/0719054

[6] P. Basso, “Optimal Search for the Global Maximum of Function with Bounded Seminorm,” SIAM Journal on Numerical Analysis, Vol. 22, No. 5, 1985, pp. 888-903.
doi:10.1137/0722053

[7] F. Schoen, “On a Sequential Search Strategy in Global Optimization Problems,” Calcolo, Vol. 19, No. 3, 1982, pp. 321-334. doi:10.1007/BF02575808

[8] Z. Shen and Y. Zhu, “An Interval Version of Shubert’s Iterative Method for the Localization of the Global Maximum,” Computing, Vol. 38, No. 3, 1986, pp. 275-280. doi:10.1007/BF02240102

[9] R. Horst and H. Tuy, “On the Convergence of Global Methods in Multi extremal Optimization,” Journal of Optimization Theory and Applications, Vol. 54, No. 2, 1987, pp. 253-271. doi:10.1007/BF00939434

[10] Y. D. Sergeyev, “Global One-dimensional Optimization Using Smooth Auxiliary Functions,” Mathematical Programming, Vol. 81, No. 1, 1998, pp. 127-146.
doi:10.1007/BF01584848

[11] D. R. Jones, C. D. Perttunen and B. E. Stuckman, “Lipschitzian Optimization without the Lipschitz Constant,” Journal of Optimization Theory and Applications, Vol. 79, No. 1, 1993, pp. 157-181.
doi:10.1007/BF00941892

[12] Y. M. Danilin and S. A. Piyavskii, “An Algorithm for Finding an Absolute Minimum,” USSR Computational Mathematics and Mathematical Physics, Vol. 12, No. 4, 1967, pp. 25-37.

[13] D. Q. Mayne and E. Polak, “Outer Approximation Algorithm for Non Differentiable Optimization Problems,” Journal of Optimization Theory and Applications, Vol. 42, No. 1, 1984, pp. 19-30. doi:10.1007/BF00934131

[14] R. H. Mladineo, “An Algorithm for Finding the Global Maximum of Multimodal, Multivariate Function,” Mathematical Programming, Vol. 34, No. 2, 1986, pp. 188-200. doi:10.1007/BF01580583

[15] C. C. Meewella and D. Q. Mayne, “An Algorithm for Global Optimization of Lipschitz Functions,” Journal of Optimization Theory and Applications, Vol. 57, No. 2, 1988, pp. 307-323. doi:10.1007/BF00938542

[16] Y. G. Evtushenko, “Numerical Methods for Finding the Global Extremum of a Function,” USSR Computational Mathematical Physics, Vol. 11, No. 6, 1971, pp. 38-54.
doi:10.1016/0041-5553(71)90065-6

[17] E. A. Galperin, “The Cubic Algorithm,” Journal of Mathematical Analysis and Applications, Vol. 112, No. 2, 1985, pp. 635-640. doi:10.1016/0022-247X(85)90268-9

[18] P. Hansen, B. Jaumard and S. H. Lu, “Global Optimization of Univariate Lipschitz Functions: I. Survey and Properties,” Mathematical Programming, Vol. 55, No. 1-3, 1992, pp. 251-272. doi:10.1007/BF01581202

[19] P. Hansen, B. Jaumard and S. H. Lu, “Global Optimization of Univariate Lipschitz Functions: II. New Algorithms and Computational Comparaison,” Mathematical Programming, Vol. 55, No. 1-3, 1992, pp. 273-292.
doi:10.1007/BF01581203

[20] P. Hansen and B. Jaumard, “Lipschitz Optimization," In: R. Horst and P. M. Pardalos, Eds., Handbook of Global Optimization, Kluwer Academis Publishers, Dordrecht, 1994, pp. 407-493.

[21] R. P. Brent, “Algorithms for Minimization without Derivatives,” Prentice-Hall, Englewood Cliffs, 1973.

[22] S. E. Jacobsen and M. Torabi, “A Global Minimization Algorithm for a Class of One-Dimensional Functions,” Journal of Mathematical Analysis and Applications, Vol. 62, No. 2, 1987, pp. 310-324.
doi:10.1016/0022-247X(78)90128-2

[23] L. Breiman and A. Cutler, “A Deterministic Algorithm for Global Optimization,” Mathematical Programming, Vol. 58, No. 1-3, 1993, pp. 179-199.
doi:10.1007/BF01581266

[24] W. Baritompa and A. Cutler, “Accelerations for Global Optimization Covering Methods Using Second Derivatives,” Journal of Global Optimization, Vol. 4, No. 3, 1994, pp. 329-341. doi:10.1007/BF01098365

[25] Y. M. Danilin, “Estimation of the Efficiency of an absolute Minimum Finding Algorithm,” USSR Computational Mathematical Physics, Vol. 11, No. 4, 1971, pp. 261-267. doi:10.1016/0041-5553(71)90020-6

[26] P. Hansen, B. Jaumard and S. H. Lu, “On the Number of Iterations of Piyavskii’s Global Optimization Algorithm,” Mathematics of Operations Research, Vol. 16, No. 2, 1991, pp. 334-350. doi:10.1287/moor.16.2.334

[27] H. J. Kushner and C. G. Yin, “Stochastic Approximation Algorithm and Applications,” Springer, New York, 1997.