32 citations · 87 across the 21 of their papers we have counts for
24 papers
An Efficient Hybrid Heuristic for the Transmission Expansion Planning under Uncertainty
Yure Rocha, Teobaldo Bulhões, Anand Subramanian +1
We address the stochastic transmission expansion planning (STEP) problem under uncertainty in renewable generation capacity and demand. STEP's objective is to minimize total transm…
A Multicut Approach to Compute Upper Bounds for Risk-Averse SDDP
Joaquim Dias Garcia, Iago Leal, Raphael Chabar +1
Stochastic Dual Dynamic Programming (SDDP) is a widely used and fundamental algorithm for solving multistage stochastic optimization problems. Although SDDP has been frequently app…
QUBO.jl: A Julia Ecosystem for Quadratic Unconstrained Binary Optimization
Pedro Maciel Xavier, Pedro Ripper, Tiago Andrade +3
We present QUBO.jl, an end-to-end Julia package for working with QUBO (Quadratic Unconstrained Binary Optimization) instances. This tool aims to convert a broad range of optimizati…
Comparing BilevelJuMP.jl Formulations: Support Vector Regression Hyperparameter Tuning
Joaquim Dias Garcia, Guilherme Bodin, Alexandre Street
In this technical report, we compare multiple reformulation techniques and solvers that can be used with the Julia package BilevelJuMP. We focus on the special case of Hyperparamet…
Regularization and Optimization in Model-Based Clustering
Raphael Araujo Sampaio, Joaquim Dias Garcia, Marcus Poggi +1
Due to their conceptual simplicity, k-means algorithm variants have been extensively used for unsupervised cluster analysis. However, one main shortcoming of these algorithms is th…
BilevelJuMP.jl: Modeling and Solving Bilevel Optimization in Julia
Joaquim Dias Garcia, Guilherme Bodin, Alexandre Street
In this paper we present BilevelJuMP, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describ…
Flexible Differentiable Optimization via Model Transformations
Mathieu Besançon, Joaquim Dias Garcia, Benoît Legat +1
We introduce DiffOpt.jl, a Julia library to differentiate through the solution of optimization problems with respect to arbitrary parameters present in the objective and/or constra…
JuMP 1.0: Recent improvements to a modeling language for mathematical optimization
Miles Lubin, Oscar Dowson, Joaquim Dias Garcia +3
JuMP is an algebraic modeling language embedded in the Julia programming language. JuMP allows users to model optimization problems of a variety of kinds, including linear programm…
An Integrated Progressive Hedging and Benders Decomposition with Multiple Master Method to Solve the Brazilian Generation Expansion Problem
Alessandro Soares, Alexandre Street, Tiago Andrade +1
This paper exploits the decomposition structure of the large-scale hydrothermal generation expansion planning problem with an integrated modified Benders Decomposition and Progress…
Assessing the Cost of Network Simplifications in Long-Term Hydrothermal Dispatch Planning Models
Andrew W. Rosemberg, Alexandre Street, Joaquim Dias Garcia +3
The sustainable utilization of hydro energy relies on accurate estimates of the opportunity cost of the water. This value is calculated through long-term hydrothermal dispatch prob…
Application-Driven Learning: A Closed-Loop Prediction and Optimization Approach Applied to Dynamic Reserves and Demand Forecasting
Joaquim Dias Garcia, Alexandre Street, Tito Homem-de-Mello +1
Forecasting and decision-making are generally modeled as two sequential steps with no feedback, following an open-loop approach. In this paper, we present application-driven learni…
Multiscale Stochastic Simulation of the US Pacific Northwest Using Distributed Computing and Databases with Integrated Inflow and Variable Renewable Energy
Joaquim Dias Garcia, Guilherme Machado, André Dias +4
Modelling challenges of the United States Pacific Northwest system have grown in the last decade. Besides classical modelling difficulties such as a complex hydro cascade with many…
Application of Progressive Hedging to Var Expansion Planning Under Uncertainty
Igor Carvalho, Tiago Andrade, Joaquim Dias Garcia +1
This paper describes the application of a Progressive Hedging (PH) algorithm to the least-cost var planning under uncertainty. The method PH is a scenario-based decomposition techn…
Modeling Multiscale Variable Renewable Energy and Inflow Scenarios in Very Large Regions with Nonparametric Bayesian Networks
Julio Alberto Dias, Guilherme Machado, Alessandro Soares +1
In this paper, we propose a non-parametric Bayesian network method to generate synthetic scenarios of hourly generation for variable renewable energy(VRE) plants. The methodology c…
MathOptInterface: a data structure for mathematical optimization problems
Benoit Legat, Oscar Dowson, Joaquim Dias Garcia +1
We introduce MathOptInterface, an abstract data structure for representing mathematical optimization problems based on combining pre-defined functions and sets. MathOptInterface is…
Community Detection for Power Systems Network Aggregation Considering Renewable Variability
Raphael Araujo Sampaio, Gerson Couto Oliveira, Luiz Carlos da Costa +1
The increasing penetration of variable renewable energy (VRE) has brought significant challenges for power systems planning and operation. These highly variable sources are typical…
Reliability-Constrained Power System Expansion Planning: A Stochastic Risk-Averse Optimization Approach
Luiz Carlos da Costa, Fernanda Souza Thomé, Joaquim Dias Garcia +1
This work presents a methodology to incorporate reliability constraints in the optimal power systems expansion planning problem. Besides LOLP and EPNS, traditionally used in power…
Modelling power markets with multi-stage stochastic Nash equilibria
Joaquim Dias Garcia, Raphael Chabar
The modelling of modern power markets requires the representation of the following main features: (i) a stochastic dynamic decision process, with uncertainties related to renewable…
Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting
Mario Souto, Joaquim D. Garcia, Alvaro Veiga
In contrast with many other convex optimization classes, state-of-the-art semidefinite programming solvers are yet unable to efficiently solve large scale instances. This work aims…
A Low-Frequency Tone Sweep Method for in-Service Fault Location in Sub-Carrier Multiplexed Optical Fiber Networks
Gustavo C. Amaral, Diego C. Villafani, Andrea Baldivieso +5
We demonstrate an optical fiber fault location method based on the frequency response of the modulated fiber optical backscattered signal in a steady state low-frequency step regim…
Fast Polarization Switch for Polarization-Based Quantum Communication
Vinicius M. Lima, Felipe Calliari, Joaquim D. Garcia +4
We present a complete optoelectronic unit for polarization visualization, switching and control. The system is based on an FPGA unit and comprises: an acquisition unit containing a…
An Optimal Polarization Tracking Algorithm for Lithium-Niobate-based Polarization Controllers
Joaquim D. Garcia, Gustavo C. Amaral
We present an optimal algorithm for the three-stage arbitrary polarization tracking using Lithium-Niobate-based Polarization Controllers: device calibration, polarization state rot…
Adaptive Trend Filter via Fast Coordinate Descent
Mario Souto, Joaquim D. Garcia, Gustavo C. Amaral
Identifying the unknown underlying trend of a given noisy signal is extremely useful for a wide range of applications. The number of potential trends might be exponential, which ca…
Adaptive Filter for Automatic Identification of Multiple Faults in a Noisy OTDR Profile
Jean Pierre von der Weid, Mario H. Souto, Joaquim D. Garcia +1
We present a novel methodology able to distinguish meaningful level shifts from typical signal fluctuations. A two-stage regularization filtering can accurately identify the locati…