Finding the Minimal Root of an Equation with the Multiextremal and Nondifferentiable Left-Hand Part

A problem very often arising in applications is presented: finding the minimal root of an equation with the objective function being multiextremal and nondifferentiable. Applications from the field of electronic measurements are given. Three methods based on global optimization ideas are introduced for solving this problem. The first one uses an a priori estimate of the global Lipschitz constant. The second method adaptively estimates the global Lipschitz constant. The third algorithm adaptively estimates local Lipschitz constants during the search. All the methods either find the minimal root or determine the global minimizers (in the case when the equation under consideration has no roots). Sufficient convergence conditions of the new methods to the desired solution are established. Numerical results including wide experiments with test functions, stability study, and a real-life applied problem are also presented.

[1]  D. Dotti,et al.  Virtually zero cross-talk dual-frequency eddy current analyzer based on personal computer , 1994 .

[2]  Aimo A. Törn,et al.  Global Optimization , 1999, Science.

[3]  L. Peregrino,et al.  Time domain analysis and its practical application to the measurement of phase noise and jitter , 1996, Quality Measurement: The Indispensable Bridge between Theory and Reality (No Measurements? No Science! Joint Conference - 1996: IEEE Instrumentation and Measurement Technology Conference and IMEKO Tec.

[4]  C. Stephens,et al.  Global Optimization Requires Global Information , 1998 .

[5]  Stéphane Mallat,et al.  Zero-crossings of a wavelet transform , 1991, IEEE Trans. Inf. Theory.

[6]  B. Jaumard,et al.  On using estimates of Lipschitz constants in global optimization , 1990 .

[7]  Efim A. Galperin,et al.  The alpha algorithm and the application of the cubic algorithm in case of unknown Lipschitz constant , 1993 .

[8]  Jirí Vlach,et al.  Analysis of switched networks , 1992, Int. J. Circuit Theory Appl..

[9]  Panos M. Pardalos,et al.  State of the Art in Global Optimization , 1996 .

[10]  K. Mondal Analog and digital filters: Design and realization , 1980, Proceedings of the IEEE.

[11]  P. Pardalos,et al.  Handbook of global optimization , 1995 .

[12]  Lee D. Cosart,et al.  Time domain analysis and its practical application to the measurement of phase noise and jitter , 1996 .

[13]  Yaroslav D. Sergeyev,et al.  An Information Global Optimization Algorithm with Local Tuning , 1995, SIAM J. Optim..

[14]  Y. D. Sergeyev,et al.  Global Optimization with Non-Convex Constraints - Sequential and Parallel Algorithms (Nonconvex Optimization and its Applications Volume 45) (Nonconvex Optimization and Its Applications) , 2000 .

[15]  Y. Sergeyev On convergence of "divide the best" global optimization algorithms , 1998 .

[16]  Leo Breiman,et al.  A deterministic algorithm for global optimization , 1993, Math. Program..

[17]  Y. Sergeyev A one-dimensional deterministic global minimization algorithm , 1995 .

[18]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .

[19]  S. A. Piyavskii An algorithm for finding the absolute extremum of a function , 1972 .

[20]  Roman G. Strongin,et al.  Global optimization with non-convex constraints , 2000 .

[21]  Pasquale Daponte,et al.  An improved neural based A/D converter , 1993, Proceedings of 36th Midwest Symposium on Circuits and Systems.

[22]  B. P. Zhang,et al.  Estimation of the Lipschitz constant of a function , 1996, J. Glob. Optim..

[23]  David E. Johnson,et al.  Introduction to Filter Theory , 1976 .

[24]  Pasquale Daponte,et al.  Two methods for solving optimization problems arising in electronic measurements and electrical engineering , 1999, SIAM J. Optim..

[25]  William Baritompa,et al.  Accelerations for a variety of global optimization methods , 1994, J. Glob. Optim..

[26]  Leon O. Chua,et al.  Linear and nonlinear circuits , 1987 .

[27]  Yaroslav D. Sergeyev,et al.  Global one-dimensional optimization using smooth auxiliary functions , 1998, Math. Program..