EconPapers    
Economics at your fingertips  
 

Implementation of Augmented Lagrangian Methods for Equilibrium Problems

Mostafa Nasri (), Luiz Carlos Matioli (), Euda Mara Silva Ferreira () and Adilson Silveira ()
Additional contact information
Mostafa Nasri: McGill University
Luiz Carlos Matioli: Universidade Federal do Paraná, UFPR PPGM/PPGMNE
Euda Mara Silva Ferreira: FACEL and PPGMNE
Adilson Silveira: Universidade Tecnológica Federal do Paraná - UTFPR PPGMNE

Journal of Optimization Theory and Applications, 2016, vol. 168, issue 3, No 14, 991 pages

Abstract: Abstract Actual implementation of augmented Lagrangian algorithms requires a solution of the subproblem generated at each iterate, which is the most challenging task. In this paper, we propose two approaches to make the augmented Lagrangian algorithms, introduced in Iusem and Nasri (RAIRO Oper Res 44:5–26, 2010) for equilibrium problems, computer amenable. The first algorithm that we suggest here incorporates the Newton method and the other one benefits from the Shor subgradient method to solve the subproblems that are produced when the augmented Lagrangian algorithms are applied to the equilibrium problem. We also illustrate our findings by numerical results which are obtained when our algorithms are implemented to solve quadratic equilibrium problems and certain generalized Nash equilibrium problem, including the river basin pollution problem, a particular case of the equilibrium problem. Moreover, we compare our numerical results with those presented in Matioli et al. (Comput Optim Appl 52:281–292, 2012) and Tran et al. (Optimization 57:749–776, 2008) for the same test problems.

Keywords: Augmented Lagrangian; Equilibrium problem; Nash equilibrium problem; Newton method; Subgradient method; 90C47; 49J35 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-015-0846-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:168:y:2016:i:3:d:10.1007_s10957-015-0846-1

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-015-0846-1

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joptap:v:168:y:2016:i:3:d:10.1007_s10957-015-0846-1