Enhanced Optimization Algorithms for the Development of Microsystems

Due to the ongoing growth of microsystems' complexity, there is an urgent need for automatic optimization. In order to include it seamlessly in the customary design process, the algorithms have to be fast and robust. Calculations of the quality function call for at least one FEM-, netlist based or behavioral simulation. Thus the optimization process is a very time consuming task. This paper presents a methodology for enhancing the convergence characteristics of heuristic search methodologies. The concept is to combine direct optimization strategies with interpolation methods in such a way that a mathematical model of the quality function is successively constructed in parallel to an optimization run. Once this model has is meaningful enough, its evaluation can substitute time consuming simulation runs.

[1]  K.B.S. Prasad,et al.  A probabilistic approach to modify the complex method , 1982 .

[2]  Rainer Laur,et al.  Theoretical basis for including small as well as large deflections of quadratic membrane structures in one behavioral model , 2000, Other Conferences.

[3]  M. Matsunami,et al.  An optimization method based on radial basis function , 1997 .

[4]  Hans-Paul Schwefel,et al.  Evolution and Optimum Seeking: The Sixth Generation , 1993 .

[5]  Thomas J. Manetsch,et al.  Toward efficient global optimization in large dynamic systems-the adaptive complex method , 1990, IEEE Trans. Syst. Man Cybern..

[6]  J. A. Guin,et al.  Modification of the Complex Method of Constrained Optimization , 1968, Comput. J..

[7]  A. Iske,et al.  On the structure of function spaces in optimal recovery of point functionals for ENO-schemes by radial basis functions , 1996 .

[8]  K. Hameyer,et al.  Adaptive coupling of differential evolution and multiquadrics approximation for the tuning of the optimization process , 2000 .

[9]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[10]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[11]  M. J. Box.  A New Method of Constrained Optimization and a Comparison With Other Methods , 1965, Comput. J..

[12]  M. Repetto,et al.  A multiquadrics-based algorithm for the acceleration of simulated annealing optimization procedures , 1996 .

[13]  J. Meinguet.  An Intrinsic Approach to Multivariate Spline Interpolation at Arbitrary Points , 1979 .