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Low-Rank and Lifted Semidefinite Programming for Mixed-Integer Polynomial Power Grid Optimization
Can a local solver return the guaranteed globally optimal solution to a nonconvex mixed-integer polynomial power grid optimization problem? By mixing low-rank semidefinite programming (SDP) and moment-based lifting in the Lasserre hierarchy, this paper provides anecdotal evidence in the affirmative.
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