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Open nowPosted 184 days ago

调度算法工程师

r3c0qt6yjw/neolix58 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now调度算法工程师r3c0qt6yjw/neolix · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 184 days ago

The posting

1. 设计与实现车队调度与路径规划核心算法（VRP 及各类变体），持续优化搜索与求解性能。 2. 构建与改进路径搜索机制：启发式策略、剪枝、双向扩展、多源多终点优化等。 3. 设计算法评估与度量体系：求解时间分布、最优性 Gap、路线稳定性、空驶率/迟到率改善等关键指标。 4. 保障解可行性与一致性：时间窗、容量、车型匹配、顺序约束、限行与偏好等快速校验。 5. 抽象业务需求，形成统一约束与目标函数模型，支撑约束可插拔与快速迭代。 6. 编写高质量技术文档（问题建模、启发式说明、指标解释、调优记录），并参与生产问题排查与根因分析。

1. 本科及以上学历，计算机 / 运筹优化 / 应用数学 / 交通工程相关专业优先；3 年以上路径规划或调度算法经验； 2. 深刻理解组合优化与调度。 3. 精通路径搜索算法与加速策略。 4. 扎实的数据结构与复杂度分析：图表示（邻接/分层/压缩）、优先队列与定制比较器、空间索引、距离裁剪与预处理。 5. 具备抽象与快速学习能力：能将业务规则提炼为约束模型，并跟进开源与学术策略（例如最新路线优化启发式）实现工程落地。 6. 熟悉至少一种主力语言，比如C++。 加分项 1. 有真实 GitHub 开源贡献或技术博客/技术演讲输出。 2. 使用或二次开发 OR-Tools、OptaPlanner、GraphHopper、OSRM 等开源调度/路径规划组件经验。 3. 探索或实践过强化学习 / 图神经网络（GNN）用于路线搜索、启发式学习或节点选择策略。

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