论文标题
基于图的建模抽象，用于优化：plasmo.jl中的概念和实现
A Graph-Based Modeling Abstraction for Optimization: Concepts and Implementation in Plasmo.jl
论文作者
论文摘要
我们提出了一个基于图形的建模抽象，以进行优化，我们称为“光学”。在此抽象下，任何优化问题都被视为分层超图，其中节点代表优化子问题，边缘代表此类子问题之间的连通性。该抽象以直观的方式实现了高度复杂模型的模块化构建，促进了使用图分析工具（执行分区，聚合和可视化任务），并促进结构与分解算法的通信。我们在基于朱莉娅的软件包plasmo.jl中提供抽象的开源实现。我们提供教程示例和大量的应用程序案例研究，以说明功能。
We present a general graph-based modeling abstraction for optimization that we call an OptiGraph. Under this abstraction, any optimization problem is treated as a hierarchical hypergraph in which nodes represent optimization subproblems and edges represent connectivity between such subproblems. The abstraction enables the modular construction of highly complex models in an intuitive manner, facilitates the use of graph analysis tools (to perform partitioning, aggregation, and visualization tasks), and facilitates communication of structures to decomposition algorithms. We provide an open-source implementation of the abstraction in the Julia-based package Plasmo.jl. We provide tutorial examples and large application case studies to illustrate the capabilities.
