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Explore graph-based decomposition approaches using Plasmo.jl in this 12-minute conference talk from The Julia Programming Language. Learn how Plasmo.jl extends JuMP.jl to build structured optimization problems using graph partitioning for variables, constraints, and objective functions. Discover how to leverage the software's capabilities to create hierarchical problem structures that can be exploited by decomposition schemes like Dual Dynamic Programming. Examine the impact of modeling decisions, such as node count and aggregation level, on applying decomposition techniques. Gain insights into practical applications of graph-based decomposition in power systems, demonstrating the potential of Plasmo.jl for tackling complex optimization challenges.
