Sthochastic variational analysis applied to the energy industry

• Grant number: 19/20023-1
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2020
• End date: August 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Mathematics - Applied Mathematics
• Principal Investigator: Paulo José da Silva e Silva
• Grantee: Felipe Eduardo Atenas Maldonado
• Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID
• Associated scholarship(s): 22/02208-7 - Contemporary variants of splitting methods for large-scale optimization, BE.EP.DR

Abstract

Stochastic systems are challenging in mathematical optimization but they also have proven to be important in applications in Engineering, Economy, energy networks, and signal processing, for example. In this context the use of Stochastic Variational Analysis techniques have be proven to be important in the solution of generalized equations, optimization, and equilibrium whenever uncertainty is present. In this project we want to use the tools from Stochastic Variational Analysis in two important problems. First, we want to study the generalization of the continuous trajectories generates by differential inclusions associated with gradient and stochastic gradient descent to deal with the case of epsion-subgradients, with epsilon strictly greater than zero and still be able to analyze the convergence of the trajetories using Lyapunov ideas. Second, we want use variational ideas to derive new decomposition strategies for two stage stochastic problems where the presence of a risk measure precludes the use of traditional methods like progressive hedging. The idea is to derive new methods based on ADDM and variations focusing on problems that arise in the energy sector. (AU)

Scientific publications

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

ATENAS, FELIPE. Understanding the Douglas-Rachford splitting method through the lenses of Moreau-type envelopes. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, v. N/A, p. 30-pg., 2025-01-07. (19/20023-1)

ATENAS, FELIPE; SAGASTIZ, CLAUDIA; SILVA, PAULO J. S.; SOLODOV, MIKHAIL. A UNIFIED ANALYSIS OF DESCENT SEQUENCES IN WEAKLY CONVEX OPTIMIZATION, INCLUDING CONVERGENCE RATES FOR BUNDLE METHODS\ast. SIAM JOURNAL ON OPTIMIZATION, v. 33, n. 1, p. 27-pg., 2023-01-01. (18/24293-0, 13/07375-0, 19/20023-1)

ATENAS, FELIPE; SAGASTIZABAL, CLAUDIA. A Bundle-Like Progressive Hedging Algorithm. JOURNAL OF CONVEX ANALYSIS, v. 30, n. 2, p. 27-pg., 2023-01-01. (19/20023-1)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

MALDONADO, Felipe Eduardo Atenas. Métodos de decomposição proximal para problemas de otimização com estrutura. 2023. Doctoral Thesis - Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica Campinas, SP.