Informs Journal on Computing, 2023 BilevelJuMP.jl: Modeling and Solving Bilevel Optimization Problems in Julia In this paper, we present BilevelJuMP.jl, a new Julia package to support bilevel optimization within the JuMP framework. The package is a Julia library that enables the user to describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Because…
XXVII SNPTEE, 2023 Nickolas Gueller, João Marcos Dusi Vilela, Guilherme Meirelles Bodin de Moraes
XXVII SNPTEE, 2023 Lucas Guerreiro, Joaquim Dias Garcia, Rodrigo Benoliel, Rafael Kelman, Vinicius Justen, Yasmina El Heri, Sávio Ribeiro
Informs Journal on Computing, 2023 Flexible Differentiable Optimization via Model Transformations 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 constraints. The library builds upon MathOptInterface, thus leveraging the rich ecosystem of solvers and composing well with modeling languages like…
SPRINGER LINK, 2023 JuMP 1.0: recent improvements to a modeling language for mathematical optimization 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 programming, integer programming, conic optimization, semidefinite programming, and nonlinear programming, and handles the low-level details…
Risk-Constrained Optimal Dynamic Trading Strategies Under Short- and Long-Term Uncertainties IEEE Transactions on Power Systems, 2023 Recent market changes in power systems with high renewable energy penetration highlighted the need for complex profit maximization and hedging strategies against price volatility and generation uncertainty. This work proposes a dynamic model to represent sequential decision making in…
