Applied Mathematics and Parallel Computing: Festschrift for Klaus RitterHerbert Fischer, Bruno Riedmueller, Stefan Schäffler The authors of this Festschrift prepared these papers to honour and express their friendship to Klaus Ritter on the occasion of his sixtieth birthday. Be cause of Ritter's many friends and his international reputation among math ematicians, finding contributors was easy. In fact, constraints on the size of the book required us to limit the number of papers. Klaus Ritter has done important work in a variety of areas, especially in var ious applications of linear and nonlinear optimization and also in connection with statistics and parallel computing. For the latter we have to mention Rit ter's development of transputer workstation hardware. The wide scope of his research is reflected by the breadth of the contributions in this Festschrift. After several years of scientific research in the U.S., Klaus Ritter was ap pointed as full professor at the University of Stuttgart. Since then, his name has become inextricably connected with the regularly scheduled conferences on optimization in Oberwolfach. In 1981 he became full professor of Applied Mathematics and Mathematical Statistics at the Technical University of Mu nich. In addition to his university teaching duties, he has made the activity of applying mathematical methods to problems of industry to be centrally important. |
Contents
Informatics and the Internal Necessity for the Mathematization of | 1 |
Exhibition Organized by Klaus Ritter on the Occasion of the 125th | 23 |
An Algorithm for the Solution of the Parametric Quadratic Program | 57 |
Copyright | |
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A₁ algorithm Angewandte Mathematik approximation assumptions automatic differentiation block characterizing sequence code list component condition constraints convergence convex defined definition denote derivatives equations estimate example exponential family feasible finite forward mode function f fuzzy sets given global optimization gradient graph grid Institut für Angewandte isotonic regression iteration Lemma likelihood function linear programming Mathematical Programming Mathematik und Statistik matrix maximal method midpoint concave midpoint quasiconcave node nonlinear programming Oberwolfach objective function obtained optimal shapes optimal solution Parallel Computing parameters partition path perimeter position processors programming problem proof quadratic programming random respect reverse mode Ritter robot scan Section semilocally semistrictly quasiconcave sensor simulation solving sonar statistical Statistik Technische Universität stochastic subset t₁ Technische Universität München Theorem tion transputer trial steps trust region variables vector workstations Y₁