Gradients and optimization with constraints in economics and social sciences

 

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Detaylı Bibliyografya
Yazar: Pernice, Sergio
Materyal Türü: artículo original
Durum:Versión publicada
Yayın Tarihi:2024
Diğer Bilgiler: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.
Ülke:Portal de Revistas UCR
Kurum:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Dil:Inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/56792
Online Erişim:https://revistas.ucr.ac.cr/index.php/matematica/article/view/56792
Anahtar Kelime:Minimización con restricciones
Multiplicadores de Lagrange
Algoritmos con campos de gradientes
Minimization with constraints
Lagrange multipliers
Gradient fields algorithms