Gradients and optimization with constraints in economics and social sciences

 

שמור ב:
מידע ביבליוגרפי
מחבר: Pernice, Sergio
פורמט: artículo original
סטטוס:Versión publicada
Fecha de Publicación:2024
תיאור:Despite their widespread use in advanced analytical and numerical techniques, gradient field methods are often underrepresented in the foundational training of economists and social scientists. As machine learning and sophisticated analytical and numerical approaches gain traction, the importance of gradient methods in optimization processes becomes increasingly apparent. This oversight in academic and practical toolsets is suboptimal. This paper aims to address this gap by introducing gradient field methods both intuitively and rigorously, situating them within the context of problems commonly encountered by economists and social scientists, with a particular focus on equality constrained optimization.
País:Portal de Revistas UCR
מוסד:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
שפה:Inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/56792
גישה מקוונת:https://revistas.ucr.ac.cr/index.php/matematica/article/view/56792
מילת מפתח:Minimización con restricciones
Multiplicadores de Lagrange
Algoritmos con campos de gradientes
Minimization with constraints
Lagrange multipliers
Gradient fields algorithms