32 citations · 87 across the 21 of their papers we have counts for
14 papers · 1 filter
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…
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…
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…
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…
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…