Avoiding the Maratos Effect by Means of a Nonmonotone Line Search. II. Inequality Constrained Problems—Feasible Iterates
| Autor: | Jian L. Zhou, J. Frédéric Bonnans, André L. Tits, Eliane R. Panier |
|---|---|
| Rok vydání: | 1992 |
| Předmět: |
Numerical Analysis
Mathematical optimization Line search Inequality Applied Mathematics media_common.quotation_subject Feasible region Constrained optimization Computational Mathematics Quadratic equation Iterated function Quadratic programming media_common Mathematics Sequential quadratic programming |
| Zdroj: | SIAM Journal on Numerical Analysis. 29:1187-1202 |
| ISSN: | 1095-7170 0036-1429 |
| Popis: | When solving inequality constrained optimization problems via Sequential Quadratic Programming (SQP), it is potentially advantageous to generate iterates that all satisfy the constraints: all quadratic programs encountered are then feasible and there is no need for a surrogate merit function. (Feasibility of the successive iterates is in fact required in many contexts such as in real-time applications or when the objective function is not defined outside the feasible set.) It has recently been shown that this is, indeed, possible, by means of a suitable perturbation of the original SQP iteration, without losing superlinear convergence. In this context, the well-known Maratos effect is compounded by the possible infeasibility of the full step of one even close to a solution. These difficulties have been accommodated by making use of a suitable modification of a “bending” technique proposed by Mayne and Polak, requiring evaluation of the constraints function at an auxiliary point at each iteration.In Part I... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|