6 citations · 9 across the 10 of their papers we have counts for
6 papers · 1 filter
Analyzing Performance and Scalability of Benders Decomposition for Generation and Transmission Expansion Planning Models
David L. Cole, Michael Lau, Xinliang Dai +2
Generation and Transmission Expansion Planning (GTEP) problems co-optimize generation and transmission expansion, enabling them to provide better planning decisions than traditiona…
Benders Decomposition using Graph Modeling and Multi-Parametric Programming
Parth Brahmbhatt, David L. Cole, Victor M. Zavala +1
Benders decomposition is a widely used method for solving large optimization problems, but its performance is often hindered by the repeated solution of subproblems. We propose a f…
Graph-Based Modeling and Decomposition of Hierarchical Optimization Problems
David L. Cole, Filippo Pecci, Omar J. Guerra +3
We present a graph-theoretic modeling approach for hierarchical optimization that leverages the OptiGraph abstraction implemented in the Julia package Plasmo.jl. We show that the a…
Hierarchical Graph Modeling for Multi-Scale Optimization of Power Systems
David L. Cole, Harsha Gangammanavar, Victor M. Zavala
Hierarchical optimization architectures are used in power systems to manage disturbances and phenomena that arise at multiple spatial and temporal scales. We present a graph modeli…
Exploiting GPU/SIMD Architectures for Solving Linear-Quadratic MPC Problems
David Cole, Sungho Shin, François Pacaud +2
We report numerical results on solving constrained linear-quadratic model predictive control (MPC) problems by exploiting graphics processing units (GPUs). The presented method red…
A Julia Framework for Graph-Structured Nonlinear Optimization
David L Cole, Sungho Shin, Victor Zavala
Graph theory provides a convenient framework for modeling and solving structured optimization problems. Under this framework, the modeler can arrange/assemble the components of an…