论文标题
bileveljump.jl：朱莉娅（Julia
BilevelJuMP.jl: Modeling and Solving Bilevel Optimization in Julia
论文作者
论文摘要
在本文中，我们提出了Bileveljump，这是一个新的Julia软件包，用于支持跳跃框架中的双重优化。该软件包是朱莉娅库，它使用户可以使用跳跃代数语法描述上层和下级优化问题。由于我们的库从Jump的语法继承了一般性和灵活性，因此我们的软件包允许用户在较低级别的圆锥约束和上层层的所有跳跃限制（圆锥，二次，非线性，非线性，整数等）中建模双层优化问题。此外，用户定义的问题随后可以通过依赖于具有平衡约束（MPEC）重新制定的数学程序的各种技术来解决。由于MathOptinterface.jl的结构和dualization.jl功能，因此可以对原始问题数据进行操作。因此，所提出的软件包允许快速模型，部署，从而基于现成的混合整数线性编程和非线性求解器实验二杆模型。
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 describe both upper and lower-level optimization problems using the JuMP algebraic syntax. Due to the generality and flexibility our library inherits from JuMP's syntax, our package allows users to model bilevel optimization problems with conic constraints in the lower level and all JuMP supported constraints in the upper level (Conic, Quadratic, Non-Linear, Integer, etc.). Moreover, the user-defined problem can be subsequently solved by various techniques relying on mathematical program with equilibrium constraints (MPEC) reformulations. Manipulations on the original problem data are possible due to MathOptInterface.jl's structures and Dualization.jl features. Hence, the proposed package allows quickly model, deploy, and thereby experiment bilevel models based on off-the-shelf mixed integer linear programming and nonlinear solvers.
