arXiv cs.AI· Zehuan Chen, Chunhe Song·· 9 天前AI 评分22
ORDO：面向 MIP Presolve 的操作级轮次感知动态排序
ORDO: Operation-level Round-aware Dynamic Ordering for MIP Presolve
AI 导读
研究者提出 ORDO，将混合整数规划（MIP）的 presolve 规划重构为统一原子动作空间上的自回归序列生成，把决策对象从参数配置转为动作序列。该方法在多个未见领域实现端到端零样本加速，据称是 presolve 动作序列上的首次。部署时采用序列 racing，通过修改 SCIP 源码注入序列并记录实际执行的动作及其轮次。
正文 · 原文
Abstract:Presolve strongly affects mixed-integer programming (MIP) performance, yet learning-based methods only optimize parameter configurations and cannot express the non-commutative temporal dependencies among actions, whose default order is nearly unique on most domains, yet functionally necessary: artificially shuffling the order of the same sequence inflates the tail of the solve-time distribution by up to several-fold. We recast presolve planning as autoregressive sequence generation over a unified atomic action space, moving the decision object to action sequences; we call this framework ORDO---Operation-level Round-aware Dynamic Ordering for MIP Presolve. Its payoff is cross-domain generalization: on multiple unseen domains it attains end-to-end zero-shot speedup---to our knowledge the first for presolve action sequences---varying by domain and not explained by corpus richness, the strongest domain reaching the largest speedup once racing is added. Deployment uses sequence racing, in which candidate sequences run concurrently and the winner is kept, enabled by an execution-and-observation facility, added by modifying the SCIP source, that injects sequences along the native path and records which actions actually execute and in which round.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.11294 [cs.AI] |
| (or arXiv:2610.11294v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11294 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Zehuan Chen [view email]
[v1]
Thu, 8 Oct 2026 05:59:52 UTC (819 KB)
来源：arXiv cs.AI · arxiv.org