| Full text | |
| Author(s): |
Total Authors: 2
|
| Affiliation: | [1] Univ Sao Paulo, Inst Math & Stat, Sao Paulo, SP - Brazil
[2] Univ Fed Sao Paulo, Inst Sci & Technol, Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | OPERATIONS RESEARCH LETTERS; v. 43, n. 5, p. 484-488, SEP 2015. |
| Web of Science Citations: | 3 |
| Abstract | |
In this paper we investigate how to efficiently apply Approximate-Karush-Kuhn-Tucker proximity measures as stopping criteria for optimization algorithms that do not generate approximations to Lagrange multipliers. We prove that the KKT error measurement tends to zero when approaching a solution and we develop a simple model to compute the KKT error measure requiting only the solution of a non-negative linear least squares problem. Our numerical experiments on a Genetic Algorithm show the efficiency of the strategy. (C) 2015 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 10/19720-5 - Optimality conditions and inexact restoration |
| Grantee: | Gabriel Haeser |
| Support Opportunities: | Research Grants - Young Investigators Grants |