• W. van Ackooij and W. de Oliveira. Nonsmooth and Nonconvex Optimization via Approximate Difference-of-Convex Decompositions. To appear in Journal of Optimization Theory and Applications, 2019, DOI: 10.1007/s10957-019-01500-3

• W. de Oliveira. Proximal bundle methods for nonsmooth DC programming. To appear in Journal of Global Optimization, 2019, DOI: 10.1007/s10898-019-00755-4        Full-text view-only (Springer Nature SharedIt)

• W. de Oliveira and M. Tcheou. An inertial algorithm for DC programming. To appear in Set-Valued and Variational Analysis, 2018, DOI: 10.1007/s11228-018-0497-0.

• A. Delfino, W. de Oliveira. Outer-approximation algorithms for nonsmooth convex MINLP problems, Optimization, 2018, V.67, I 6, pp. 797-819.

• W. van Ackooij, W. de Oliveira and Y. Song. An adaptive partition-based level decomposition for solving two-stage stochastic programs with fixe-recourse. INFORMS Journal on Computing, 2018, V. 30, I.1 pp. 57-70.

• W. de Oliveira. Target radius method for nonsmooth convex optimization. Operations Research Letters, 2017, V. 45, I. 6, pp. 659-664 

• F.B. Rodríguez, W. de Oliveira and E. Finardi. Application of scenario tree reduction via quadratic process distances to medium-term hydrothermal scheduling problem IEEE Transactions on Power Systems, 2017, Volume 32, Issue 6, pp. 4351-436.

• V.B. Bruno, L.A.M. Moraes and W. de Oliveira. Optimization techniques for the Brazilian natural gas network planning problem. Energy Systems (ENSY), 2017, Volume 8, Issue 1, pp. 81-101.

• W. van Ackooij, V. Berge, W. de Oliveira and C. Sagastizábal. Probabilistic optimization via approximate p-efficient points and bundle methods. Computers & Operations Research, 2017, V. 77, pp. 177-193. 

• J. Malick, W. de Oliveira, S. Zaourar.Uncontrolled inexact information within bundle methods. EURO Journal on Computational Optimization, 2017, V. 5, pp. 5-29.

• W. van Ackooij, A. Frangioni, W. de Oliveira. Inexact stabilized Benders' decomposition approaches with application to chance-constrained problems with finite support. Computational Optimization and Applications, 2016, Volume 65, Issue 3, pp. 637-669 

• W. van Ackooij and W. de Oliveira. Convexity and optimization with copulae structured probability constraints Optimization, 2016, Volume 65, Issue 7, pp. 1349-1376.

• W. de Oliveira. Regularized optimization methods for convex MINLP problems. TOP (Operations Research & Decision Theory), 2016, V. 24, Issue 3, pp. 665-692

• J.Y. Bello Cruz and W. de Oliveira. On weak and strong convergence of the projected gradient method for convex optimization in real Hilbert spaces. Numerical Functional Analysis and Optimization, 2016, Volume 37, 2, pp. 129-144.

• W. de Oliveira and M. Solodov. A doubly stabilized bundle method for nonsmooth convex optimization. Mathematical Programming, 2016, Volume 156, Issue 1, pp 125-159. 

• W. van Ackooij, J.Y. Bello Cruz, W. de Oliveira. A strongly convergent proximal bundle method for convex minimization in Hilbert spaces. Optimization, 2016, Volume 65, Issue 1, pp. 145-167.

• W. de Oliveira, C Sagastizábal and C. Lemaréchal. Convex proximal bundle methods in depth: a unified analysis for inexact oracles. Mathematical Programming, 2014, V. 148, Issue 1-2, pp 241-277

• W. de Oliveira, C. Sagastizábal. Bundle methods in the XXIst century: a birds'-eye view. Pesquisa Operacional, 2014, Volume 34 Issue 3, pp 647-670

• W. de Oliveira, C. Sagastizábal. Level bundle methods for oracles with on-demand accuracy. Optimization Methods & Software, 2014, Volume 29, Issue 6, pp 1180-1209 

• W. van Ackooij and W. de Oliveira. Level bundle methods for constrained convex optimization with various oracles. Computational Optimization and Applications, 2014, Volume 57, Issue 3, pp 555-597

• J. Y. Bello Cruz and W. de Oliveira. Level bundle-like algorithms for convex optimization. Journal of Global Optimization, August 2014, Volume 59, Issue 4, pp 787-809. 

• W. de Oliveira, C. Sagastizábal, and S. Scheimberg. Inexact bundle methods for two-stage stochastic programming. SIAM Journal on Optimization, v. 21, p. 517-544, 2011. 

• W. de Oliveira, C. Sagastizábal, et al. Optimal scenario tree reduction for stochastic streamflows in power generation planning problems. Optimization Methods & Software, 2010, V 25 pp. 917-936

• G. Bonvin, S. Demassey, W. de Oliveira. Robust design of pumping stations in water distribution networks. Proceeding of 6th World Congress on Global Optimization. Seris Advances in Intelligent Systems and Computing, Springer-Verlag, 2019.

• B. Schelk,  W. de Oliveira. Interpolação de imagens via minimização da função da variação total suavizada. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, v.6, n.1, 2018.

• W. de Oliveira. Combining level and proximal bundle methods for convex optimization in energy problems. EngOpt - International Conference on Engineering Optimization, Rio de Janeiro, Brazil, 2012. 

• W. de Oliveira, C. Sagastizábal, et al. Optimal scenario tree reduction for stochastic streamflows in power generation planning problems. EngOpt - International Conference on Engineering Optimization, Rio de Janeiro, Brazil, 2008.  

• J.M. Damázio, M.E.P. Maceira, D.D.J. Penna and W. de Oliveira. Validation of streamflow scenarios for scheduling in the Brazilian hydro thermal electric generation system. Hydropredict - International Conference on Predictions for Hydrology, Ecology and Water resources Management. pp. 345-348. Prague, Czech Republic, 2008.

• M.E.P. Maceira, J.M Damázio, W. de Oliveira and D.D.J. Penna. Compatibilidade entre cenários sintéticos de vazões e energias utilizados no planejamento da operação de curto e médio prazos. XX SNPTEE - Seminário nacional de produção e transmissão de energia, Recife, Brasil, 2009. 

• W. de Oliveira, D.D.J. Penna J.M. Damázio and M.E.P. Maceira. Análise da correlação cruzada através da distribuição lognormal três parâmetros. XVII ABRH - Simpósio brasileiro de recursos hídricos, Campo Grande, Brasil, 2009. 

• W. de Oliveira, C. Sagastizábal, D.D.J. Penna, J.M. Damázio and M.E.P. Maceira. Redução ótima de cenários de vazões afluentes aos reservatórios. XVII ABRH - Simpósio brasileiro de recursos hídricos, São Paulo, Brasil, 2007. 

• W. de Oliveira, C. Sagastizábal, D.D.J. Penna, J.M. Damázio and M.E.P. Maceira.Técnicas de redução de cenários de vazões aplicadas ao planejamento da operação de curto prazo. XIX SNPTEE - Seminário nacional de produção e trasnmissão de energia, Rio de Janeiro, Brasil, 2007. 

Dissertations and Technical Reports 

• W. de Oliveira.  Nonsmooth optimization and stochastic programming: from theory to practice. Habilitation à Diriger des Recherches en Mathématiques Appliquées, Université Paris 1 Panthéon Sorbonne, Paris, 2018 (Slides)

• W. de Oliveira.  Inexact Bundle Methods Applied to Stochastic Programming. (In portuguese). Ph.D Thesis - Universidade Federal do Rio de Janeiro, 2011

• W. de Oliveira. Optimal Scenario Reduction in Stochastic Programming. Application to Streamflows in Power Generation Planning Problems. (In portuguese). Dissertation (Mater's in Mathematics) - Instituto Nacional de Matemática Pura e Aplicada. Série B-16-Agosto/2007.

• W. de Oliveira and J. Eckestein. A bundle method for exploiting additive structure in difficult optimization problems. Technical Report - Optimization Online, 2015