This volume contains the proceedings of the fifth conference on Parametric Optimization and Related Topics, held in Tokyo, Japan, from October 6-10, 1997. Parametric optimization as a part of mathematical programming investigates the behaviour of solutions to optimization problems under data perturbations. Properties involved, such as continuity, differentiability, topological stability and structural stability play a fundamental role in a series of further questions that are of interest both from a practical and a theoretical point of view. Many connections with other disciplines of operations research, like stochastic programming, model-building, numerical methods and optimal control originate from these properties. The presented papers (all refereed) are topical and original studies reflecting recent results in current directions of research in theory and applications.
Frankfurt/M., Berlin, Bern, Bruxelles, New York, Oxford, Wien, 2000. 250 pp., num. fig.
Contents: A. Antipin: Gradient-Proximal Method of Solving of Extreme Inclusions – D. Augustin/H. Maurer: An Example for Computational
Sensitivity Analysis of State Constrained Control Problems – E. Belousov: On Continuity of Point-to-Set Mappings associated
with the Penalty-Function Method – S. Dempe/S. Vogel: The Subdifferential of the Optimal Solution in Parametric Optimization
– T. Fujie/ R. Hirabayashi/Y. Ikebe/Y. Shinano: Stable Set Polytopes in a Higher Dimensional Space – R. Henrion/W. Römisch:
Stability of Solutions to Chance Constrained Stochastic Programs – Y. Kimura/ K. Tanaka: Some Dynamic Decision Process – U.
Klemt: Sufficient Optimality Conditions and Stability Analysis for a Class of Multidimensional Control Problems – L. Neralić:
Sensitivity in Data Envelopment Analysis for Arbitrary Perturbations of All Data in the Charnes-Cooper-Rhodes Model – O. Stein:
The Reduction Ansatz in Absence of Lower Semi-Continuity – T. Takahama/S. Sakai: Multiobjective Nonlinear Optimization Method
«Vector Simplex» – H. Tuy: On Parametric Methods in Global Optimization – H. Yamashita/H. Yabe: A Primal-Dual Interior Point
Method for Nonlinear Optimization: Global Convergence, Convergence Rate and Numerical Performance for Large Scale Problems.