Plasmo.jl
Graph-Based Modeling and Simulation of Complex Systems. We present graph-based modeling abstractions to represent cyber-physical dependencies arising in complex systems. Specifically, we propose an algebraic graph abstraction to capture physical connectivity in complex optimization models and a computing graph abstraction to capture communication connectivity in computing architectures. The proposed abstractions are scalable and are used as the backbone of a Julia -based software package that we call Plasmo.jl . We show how the algebraic graph abstraction facilitates the implementation, analysis, and decomposition of optimization problems and we show how the computing graph abstraction facilitates the implementation of optimization and control algorithms and their simulation in virtual environments that involve distributed, centralized, and hierarchical computing architectures.
Keywords for this software
References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
Sorted by year (- Abhyankar, Shrirang; Betrie, Getnet; Maldonado, Daniel Adrian; Mcinnes, Lois C.; Smith, Barry; Zhang, Hong: PETSc DMNetwork: a library for scalable network PDE-based multiphysics simulations (2020)
- Cao, Yankai; Zavala, Victor M.: A scalable global optimization algorithm for stochastic nonlinear programs (2019)
- Jordan Jalving, Yankai Cao, Victor M. Zavala: Graph-Based Modeling and Simulation of Complex Systems (2018) arXiv