Quantum Approximate Optimization Algorithm (QAOA)
The optimization sibling of VQE: encode a combinatorial problem as an energy landscape and use quantum interference to hunt for low-energy solutions.
QAOA, the quantum approximate optimization algorithm, is the optimization-flavored sibling of VQE. Encode a combinatorial problem (scheduling, routing, portfolio selection) into an energy landscape, then alternate between two quantum operations, with a classical loop tuning the schedule. Good solutions correspond to low energies; the hope is that quantum interference finds them faster than classical heuristics.
'Hope' is doing real work in that sentence. QAOA is wildly popular as a benchmark because it's simple and maps to almost anything, but evidence of genuine advantage over the best classical solvers remains elusive. When a press release says a quantum computer 'optimized logistics,' QAOA is usually under the hood, and the unasked question is usually 'compared to what?'
The millikelvin's house rule: optimization claims earn skepticism until the classical baseline is named.