Preprint
Aug 2026
Learning Early-to-Final Solution Consistency for MILP Acceleration
This paper finds that solutions produced at the early search stage of MILP solvers are often structurally close to the solutions found after full-budget search, and proposes a new solver-informed paradigm that shifts the learning target from variable assignment to early-to-final consistency.
Guanli Li, Chengrui Gao, Chenguang Wang et al.
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