Publisher's Synopsis
This volume is intended for readers who are familiar with the basic approaches and methods of mathematical optimization. The subject matter is concerned with optimization problems in which some or all of the individual data involved depend on one parameter. This book considers thwe applications of solution algorithms for one-parameter optimization problems in the following fields: globally convergent algorithms for nonlinear, in particular non-convex, optimization problems, global optimization and multiobjective optimization.;The main tool for a solution algorithm for a one-parametric optimization problem used is the so-called pathfollowing methods. Classical methods in the set of statianory points will be extended to the set of all generalized critical points. The book contains theoretical background information and introduces two generic classes. It also discusses the jump from one connected component in the set of local minimizers and generalized critical points to another one.
