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DCEmbed is proposed, a heuristic for optimization problems with embedded neural surrogates that leverages the difference-of-convex (DC) representation of the network and avoids adding activation binaries, and demonstrates much faster progress toward high-quality feasible solutions than approaches using exact mixed-inte...
A dependency-graph framework is proposed to formalize compositional reasoning, yielding three levels of compositionality with increasing complexity, and preliminary evidence that the decomposed-to-composed asymmetry can extend to practical settings is presented.
This work develops FLARE (Formulation-Level Automated Reformulation Evaluation), a method that uses an LLM-based agent and the Lean proof assistant to verify proposed reformulations against a reference formulation to enable reliable verification in automated optimization modeling.
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