RT Report
T1 Optimizing initial guesses to improve global minimization
A1 Ivorra, Benjamín Pierre Paul
A1 Mohammadi, Bijan
A1 Ramos Del Olmo, Ángel Manuel
AB In this paper, we envision global optimization as finding, for a given calculation complexity, a suitable initial guess of a considered optimization algorithm. One can imagine that this possibility clearly improve the capacity of existing optimization algorithms, including stochastic ones. This approach is validated on several large dimension nonlinear minimization problems. Results are compared with those obtained by a geneti algorithm
PB Departamento de Matemática Aplicada, Universidad Complutense
YR 2008
FD 2008
LK https://hdl.handle.net/20.500.14352/56490
UL https://hdl.handle.net/20.500.14352/56490
LA eng
NO Institut de Mathématiques et de Modélisation de Montpellier
NO Ministerio de Educación y Ciencia (España)
NO Dirección General de Universidades e Investigación (Comunidad de Madrid)
NO Universidad Complutense
DS Docta Complutense
RD 8 abr 2025