RT Conference Proceedings
T1 On Augmented Lagrangeans in Linear Programming (LP) Phase I
A1 Guerrero-García, Pablo
A1 Hendrix, Eligius María Theodorus
A1 Rocha, Ana M.A.C
K1 Optimización matemática
AB The concept of linking constraints to an objective in optimization problems was found due to Lagrange in the 19th century. The so-called Lagrange multipliers were related to duality theory in the 20th century. At the same time, ideas from penalty methods were linked with ideas of the Lagrangean called Augmented Lagrangean (AL) methods. The concepts have been applied to Nonlinear Optimization, Global Optimization and also even recent to Linear Programming (LP) [1]. This paper focuses on the latter question of how AL methods can be applied efficiently to find initial feasible solutions as a starting point in scarce LP procedures. In this contribution, we will expose our findings of applying methods to Linear Programming methods. [1]  Ivet L. Galabova and Julian A. J. Hall. The ‘idiot’ crash quadratic penalty algorithm for linear programming and its application to linearizations of quadratic assignment problems. Optimization Methods and Software, 35(3):488–501, May 2020.
YR 2023
FD 2023-07-24
LK https://hdl.handle.net/10630/28557
UL https://hdl.handle.net/10630/28557
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026