Welington De Oliveira

Publication(s)

• 2026
  Scenario tree reduction via Wasserstein barycenters DOI : 10.1007/s10479-026-07062-8
• 2026
  Measuring dissimilarity between convex cones by means of max-min angles DOI : 10.1137/25M1794371
• 2025
  Methods of Non-smooth Optimization in Stochastic Programming From Conceptual Algorithms to Real-World Applications DOI : 10.1007/978-3-031-84837-7
• 2025
  A Progressive Decoupling Algorithm for Minimizing the Difference of Convex and Weakly Convex Functions DOI : 10.1007/s10957-024-02574-4
• 2025
  DERIVATIVE-FREE APPROACHES FOR CHANCE-CONSTRAINED PROBLEMS WITH RIGHT-HAND SIDE UNCERTAINTY DOI : 10.1137/23M1622635
• 2025
  A Proximal-Type Method for Nonsmooth and Nonconvex Constrained Minimization Problems DOI : 10.1007/s10957-024-02597-x
• 2025
  Algorithms for nonsmooth optimization models under distance-to-set penalties DOI : 10.1080/02331934.2025.2567647
• 2024
  Computing Critical Angles Between Two Convex Cones DOI : 10.1007/s10957-024-02424-3
• 2024
  Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals DOI : 10.1137/23M1584228
• 2023
  S-BORM: Reliability-based optimization of general systems using buffered optimization and reliability method DOI : 10.1016/j.ress.2023.109314
• 2023
  Difference-of-Convex approach to chance-constrained Optimal Power Flow modelling the DSO power modulation lever for distribution networks DOI : 10.1016/j.segan.2023.101168
• 2022
  Improving the performance of the stochastic dual dynamic programming algorithm using Chebyshev centers DOI : 10.1007/s11081-020-09558-z
• 2022
  Short Paper - A note on the Frank-Wolfe algorithm for a class of nonconvex and nonsmooth optimization problems DOI : 10.5802/ojmo.21
• 2022
  Addendum to the paper ‘Nonsmooth DC-constrained optimization: constraint qualification and minimizing methodologies’ DOI : 10.1080/10556788.2022.2063861
• 2022
  A derivative-free trust-region algorithm with copula-based models for probability maximization problems DOI : 10.1016/j.ejor.2021.09.040
• 2022
  Revisiting augmented Lagrangian duals DOI : 10.1007/s10107-021-01703-5
• 2021
  Risk-Averse Stochastic Programming and Distributionally Robust Optimization Via Operator Splitting DOI : 10.1007/s11228-021-00600-5
• 2021
  Two-stage and multi-stage decompositions for the medium-term hydrothermal scheduling problem: A computational comparison of solution techniques DOI : 10.1016/j.ijepes.2020.106659
• 2021
  A bundle method for nonsmooth DC programming with application to chance-constrained problems DOI : 10.1007/s10589-020-00241-8
• 2020
  Robust Design of Pumping Stations in Water Distribution Networks DOI : 10.1007/978-3-030-21803-4_95
• 2020
  Sequential Difference-of-Convex Programming DOI : 10.1007/s10957-020-01721-x
• 2020
  Asynchronous level bundle methods DOI : 10.1007/s10107-019-01414-y
• 2020
  Some brief observations in minimizing the sum of locally Lipschitzian functions DOI : 10.1007/s11590-019-01477-y
• 2020
  A mixed-integer and asynchronous level decomposition with application to the stochastic hydrothermal unit-commitment problem DOI : 10.3390/a13090235
• 2020
  The ABC of DC Programming DOI : 10.1007/s11228-020-00566-w
• 2020
  Bundle methods for inexact data DOI : 10.1007/978-3-030-34910-3_12
• 2020
  A Stochastic Optimization Model for Frequency Control and Energy Management in a Microgrid DOI : 10.1007/978-3-030-64583-0_17
• 2020
  A sequential partial linearization algorithm for the symmetric eigenvalue complementarity problem DOI : 10.1007/s10589-020-00226-7
• 2019
  Non-smooth DC-constrained optimization: constraint qualification and minimizing methodologies DOI : 10.1080/10556788.2019.1595619
• 2019
  An Inertial Algorithm for DC Programming DOI : 10.1007/s11228-018-0497-0
• 2019
  On level regularization with normal solutions in decomposition methods for multistage stochastic programming problems DOI : 10.1007/s10589-019-00104-x
• 2019
  Nonsmooth and Nonconvex Optimization via Approximate Difference-of-Convex Decompositions DOI : 10.1007/s10957-019-01500-3
• 2019
  Proximal bundle methods for nonsmooth DC programming DOI : 10.1007/s10898-019-00755-4
• 2018
  Outer-approximation algorithms for nonsmooth convex MINLP problems DOI : 10.1080/02331934.2018.1434173
• 2018
  Adaptive partition-based level decomposition methods for solving two-stage stochastic programs with fixed recourse DOI : 10.1287/ijoc.2017.0765
• 2017
  Target radius methods for nonsmooth convex optimization DOI : 10.1016/j.orl.2017.10.010
• 2017
  Uncontrolled inexact information within bundle methods DOI : 10.1007/s13675-015-0060-9
• 2017
  Optimization techniques for the Brazilian natural gas network planning problem DOI : 10.1007/s12667-015-0172-6
• 2017
  Probabilistic optimization via approximate p-efficient points and bundle methods DOI : 10.1016/j.cor.2016.08.002
• 2017
  Application of Scenario Tree Reduction Via Quadratic Process to Medium-Term Hydrothermal Scheduling Problem DOI : 10.1109/TPWRS.2017.2658444
• 2016
  A strongly convergent proximal bundle method for convex minimization in Hilbert spaces DOI : 10.1080/02331934.2015.1004549
• 2016
  Regularized optimization methods for convex MINLP problems DOI : 10.1007/s11750-016-0413-4
• 2016
  A doubly stabilized bundle method for nonsmooth convex optimization DOI : 10.1007/s10107-015-0873-6
• 2016
  Inexact stabilized Benders’ decomposition approaches with application to chance-constrained problems with finite support DOI : 10.1007/s10589-016-9851-z
• 2016
  Convexity and optimization with copulæ structured probabilistic constraints DOI : 10.1080/02331934.2016.1179302
• 2016
  On weak and strong convergence of the projected gradient method for convex optimization in real hilbert spaces DOI : 10.1080/01630563.2015.1080271
• 2014
  Level bundle methods for oracles with on-demand accuracy DOI : 10.1080/10556788.2013.871282
• 2014
  Level bundle-like algorithms for convex optimization DOI : 10.1007/s10898-013-0096-4
• 2014
  Bundlemethods in the XXIst century: A bird’s-eye view DOI : 10.1590/0101-7438.2014.034.03.0647
• 2014
  Level bundle methods for constrained convex optimization with various oracles DOI : 10.1007/s10589-013-9610-3
• 2014
  Convex proximal bundle methods in depth: a unified analysis for inexact oracles DOI : 10.1007/s10107-014-0809-6
• 2011
  Inexact bundle methods for two-stage stochastic programming DOI : 10.1137/100808289
• 2010
  Optimal scenario tree reduction for stochastic streamflows in power generation planning problems DOI : 10.1080/10556780903420135

Projects

• 2025-2026 Computational Toolbox for Linear Optimization with Joint Affine Chance Constraints Lead Investigator Ce projet portait sur les problèmes d’optimisation linéaire avec contraintes probabilistes conjointes, une classe de programmes stochastiques rencontrée notamment dans l’énergie, la finance et les transports. L’objectif principal était de développer un logiciel libre en Julia dédié à la résolution de ces problèmes, intégrant des algorithmes d’optimisation, des outils d’évaluation et de différentiation des probabilités, ainsi qu’une bibliothèque de problèmes tests. Le projet visait également à renforcer les fondements méthodologiques de cette classe de modèles et à diffuser les résultats au sein de la communauté scientifique. Le projet a été financé par le programme PGMO (Gaspard Monge pour l’Optimisation, la Recherche Opérationnelle et leurs interactions avec la Science des Données).
• 2021 Models for planning energy investiment under uncertainty Lead Investigator Ce projet portait sur le développement de nouveaux algorithmes d’optimisation pour la résolution de problèmes d’optimisation stochastique multiétapes issus de la planification énergétique. L’objectif était de concevoir des modèles et des méthodes numériques permettant de soutenir les décisions d’investissement à long terme dans un contexte d’incertitude.

Teaching

PhD supervision

• 2025 Méthodes d'exploitation de la structure pour l'optimisation stochastique à grande échelle GARRISI Charles
• 2022 Gestion prévisionnelle optimisée sous incertitudes jointes - CIFRE avec EDF SYRTSEVA Ksenia
• 2022 Avancées algorithmiques pour l'optimisation contrainte non lisse et non convexe MARTíNEZ SEMPERE Gregorio
• 2022 Optimisation Multi-Étapes sous Incertitude : de la Réduction d'Arbres de Scénarios par Transport Optimal à l'Optimisation Robuste - Projet industriel avec IFPEN MIMOUNI Daniel
• 2018 Prise en compte des incertitudes dans la gestion prévisionnelle court-terme - CIFRE avec EDF JAVAL Paul