---
id: 20260724-T0-06
title: "MILP-Evo：全自动闭环设计混合整数规划求解器"
title_en: "MILP-Evo Automatically Designs MILP Solvers in a Closed-Loop System"
url: https://ai.daily.yangsir.net/daily/20260724-T0-06
issue_date: 2026-07-24
publish_date: 2026-07-23T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2607.18252
---

# MILP-Evo：全自动闭环设计混合整数规划求解器

arXiv 新论文提出 MILP-Evo 框架，利用闭环自动设计方法生成高性能混合整数线性规划（MILP）求解器。传统机器学习加速 MILP 的方案难以检查和部署，而 MILP-Evo 通过可解释的策略表示和进化搜索，自动生成可直接运行的求解器代码。在标准测试集上超过多个手工设计的求解器，对运筹优化领域具有实用价值。

## English Version

**MILP-Evo Automatically Designs MILP Solvers in a Closed-Loop System**

A new arXiv paper presents MILP-Evo, a closed-loop framework that automatically designs high-performance MILP solvers. Unlike black-box ML approaches, it produces interpretable, deployable solver code via evolutionary search. It outperforms several hand-crafted solvers on standard benchmarks, offering a practical path for optimization practitioners.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2607.18252)

**详情页**：https://ai.daily.yangsir.net/daily/20260724-T0-06

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