FilterDDP is a line-search filter differential dynamic programming algorithm for discrete-time optimal control problems with nonlinear equality constraints, featuring two specific design choices for robustness, a local quadratic convergence proof, a primal-dual interior-point extension for mixed-con
JuMP 1.0: Recent improvements to a modeling language for mathematical optimization,
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A scalable PTDF-based two-stage optimization framework with trust-region multicut Benders decomposition for co-optimizing transmission and storage under high renewables, demonstrated on a 2000-bus synthetic Texas system with sub-2% optimality gaps.
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Line-Search Filter Differential Dynamic Programming for Optimal Control with Nonlinear Equality Constraints
FilterDDP is a line-search filter differential dynamic programming algorithm for discrete-time optimal control problems with nonlinear equality constraints, featuring two specific design choices for robustness, a local quadratic convergence proof, a primal-dual interior-point extension for mixed-con
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High-Resolution PTDF-Based Planning of Storage and Transmission Under High Renewables
A scalable PTDF-based two-stage optimization framework with trust-region multicut Benders decomposition for co-optimizing transmission and storage under high renewables, demonstrated on a 2000-bus synthetic Texas system with sub-2% optimality gaps.