Publications - Welington de Oliveira

Publications

Articles under review in scientific journals

E. Butyn, E.W. Karas, W. de Oliveira A derivative-free trust-region algorithm with copula-based models for probability maximization problem

Articles published or accepted for publication in scientific journals

M. Cordova, W. de Oliveira, C. Sagastizábal Revisiting Augmented Lagrangian Duals.To appear in Mathematical Programming, 2021.

W. de Oliveira Risk-averse stochastic programming and distributionally robust optimization via operator splitting. To appear in Set-Valued and Variational Analysis, 2021. DOI: 10.1007/s11228-021-00600-5

F. Beltrán, E.C. Finardi, W. de Oliveira. Two-stage and multi-stage decompositions for the medium-term hydrothermal scheduling problem: a computational comparison of solution techniques. International Journal of Electrical Power & Energy Systems, 127, 106659 2021.

W. van Ackooij, S. Demassey, P. Javal, H. Morais, W. de Oliveira, and B. Swaminathan A bundle method for nonsmooth DC programming with application to chance-constrained problems. Computational Optimization and Applications, Volume 78, pp. 451-490, 2021.

F. Beltrán, E.C. Finardi, G. Fredo, W. de Oliveira. Improving the performance of the stochastic dual dynamic programming algorithm using Chebyshev centers. To appear in Optimization and Engineering, DOI: 10.1007/s11081-020-09558-z, 2020.

M. Fukushima, J. Júdice, W. de Oliveira, V. Sessa. A sequential partial linearization algorithm for the symmetric eigenvalue complementarity problem. Computational Optimization and Applications, Volume 77, pp. 711–728, 2020.

W. de Oliveira The ABC of DC Programming. Set-Valued and Variational Analysis, Volume 28, pp. 679-706, 2020.

B. Colonetti, E.C. Finardi, W. de Oliveira. A mixed-integer and asynchronous level decomposition with application to the stochastic hydrothermal unit-commitment problem. Algorithms, 2020, Volume 13, Number 235. In Honor of the 60th Birthday of Adil M. Bagirov.

F. Iutzeler, J. Malick and W. de Oliveira. Asynchronous level bundle methods. Mathematical Programming, Volume 184, pp. 319–348, 2020.

W. de Oliveira. Sequential Difference-of-Convex Programming. Journal of Optimization Theory and Applications, 2020, Volume 186, Issue 3, pp. 936-959.
Supplemental Material: Numerical experiments and Matlab code.

W. van Ackooij and W. de Oliveira. Some brief observations in minimizing the sum of locally Lipschitzian functions. Optimization Letters, 2020, Volume 14 pp. 509-520.

W. de Oliveira and M. Tcheou. An inertial algorithm for DC programming. Set-Valued and Variational Analysis, 2019, Volume 27, Issue 4, pp. 895-919

W. de Oliveira. Proximal bundle methods for nonsmooth DC programming. Journal of Global Optimization, 2019, Volume 75, Issue 2, pp. 523-563. Best paper award: info

W. van Ackooij, W. de Oliveira and Y. Song. On regularization with normal solutions in decomposition methods for multistage stochastic programming. Computational Optimization and Applications, 2019, Volume 74, Issue 1, pp. 1-42.

W. van Ackooij and W. de Oliveira. Nonsmooth and Nonconvex Optimization via Approximate Difference-of-Convex Decompositions. Journal of Optimization Theory and Applications, 2019, Volume 182, Issue 1 pp. 49-80

W. van Ackooij and W. de Oliveira. Nonsmooth DC-constrained optimization: constraint qualification and minimizing methodologies. Optimization Methods and Software, 2019, Volume 34, Issue 4 pp. 890-920. This version corrects and expands Section 2 of the original paper.

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. Best paper award: info

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, D.D.J. Penna, M.E.P. Maceira and J.M. Damázio et al. Optimal scenario tree reduction for stochastic streamflows in power generation planning problems. Optimization Methods & Software, 2010, V 25 pp. 917-936

Chapters of books

D. Bousnina, W. de Oliveira and P. Flaum. A stochastic optimization model for frequency control and energy management in a microgrid. Machine Learning, Optimization, and Data Science, Springer International Publishing, 2020, pp. 177-189.

W. de Oliveira and M. Solodov. Bundle methods for inexact data. Numerical Nonsmooth Optimization: State of the Art Algorithms. A. Bagirov, M. Gaudioso, N. Karmitsa and M. Mäakelä (editors). Springer, Chapter 12, 2020.

G. Bonvin, S. Demassey, W. de Oliveira. Robust design of pumping stations in water distribution networks. In: Le Thi H., Le H., Pham Dinh T. (eds) Optimization of Complex Systems: Theory, Models, Algorithms and Applications. WCGO 2019. Advances in Intelligent Systems and Computing, vol 991. Springer, Cham, 2020, pp 957-967.

Articles published in Annals of events

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. Best Thesis award: info

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

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