arXiv Machine Learning November 5, 2026 By Benjamin Jacob Bodner

Adaptive Multi Mode: Budget-Aware Routing of Optimizers By Online Landscape Probes

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The paper introduces Adaptive Multi Mode (AMM), a budget‑aware router that selects among several optimization engines—quasi‑Newton, trust‑region, coordinate, multistart, and evolution‑strategy—based on online probes of the problem landscape. Each probe evaluates features such as curvature, plateaus, separability, kinks, basins, and fractal structure, and is assigned a validity range and cost relative to the budget. In extensive pre‑registered tests on the bbob benchmark, AMM achieved the highest target share in 382 of 600 function‑dimension‑budget cells, outperforming up to seven competitors and maintaining strong performance across transformations and constraints.

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