CP-WSP：面向可配置多约束员工排班的声明式CP-SAT框架
CP-WSP: A Declarative CP-SAT Framework for Configurable Multi-Constraint Workforce Scheduling
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中文总结 AI 辅助
针对现有员工排班约束建模能力不足的问题，提出CP-WSP声明式CP-SAT框架，支持多类缺失的关键约束，可通过JSON配置实现合规排班与多目标优化，提供可复现基准套件。
中文摘要 AI 辅助
员工排班是一类NP难组合优化问题，需要同时满足劳动法规、覆盖要求、员工偏好与运营目标。现有约束规划（CP）公式通常仅能建模包含6至12个约束的简化班次粒度实例，严重缺乏对以下内容的显式支持：带中点位置控制的强制休息排班、 acuity加权工作量公平性、支持需求驱动人员配置的子班次时间粒度、跨周排班稳定性，以及24小时运营场景中常见的跨夜班模式。本文提出CP-WSP：一种声明式CP-SAT框架，可将14项硬约束作为数学上不可违反的要求强制执行（从构造层面保证零违规），同时通过统一加权惩罚函数优化15项软目标——所有功能均可通过JSON规范配置，无需修改代码。核心贡献包括：支持带中心性控制的强制休息排班的班次窗口变量分解方法、 acuity加权工作量公平性机制、覆盖30分钟至2小时的多粒度时间分辨率、跨周排班稳定性、适用于跨夜班的网格偏移预处理技术，以及供社区对比使用的可复现36配置基准套件。研究在小时级与班次级粒度的INRC-II基准集及36种合成配置上完成了评估。
英文摘要
Workforce scheduling is an NP-hard combinatorial optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, employee preferences and operational objectives. Existing CP formulations typically model simplified instances with 6-12 constraints at shift-level granularity and critically lack explicit support for: mandatory break scheduling with midpoint placement control; acuity weighted workload equity; sub-shift temporal granularity enabling demand-driven staffing; inter-week schedule stability; and cross-midnight shift patterns common in 24-hour operations. This paper presents CP-WSP: a declarative CP-SAT framework enforcing 14 hard constraints as mathematically inviolable requirements (zero regulatory violations by construction) while optimizing 15 soft objectives through a unified weighted penalty function -- all configurable via a JSON specification with no code changes required. Key contributions include: a shift-window variable decomposition enabling mandatory break scheduling with centrality control; acuity-weighted workload equity; multi-granularity temporal resolution from 30 minutes to 2 hours; inter-week schedule stability; a grid-offset preprocessing technique for cross-midnight shifts; and a reproducible 36-configuration benchmark suite for community comparison. Evaluated on INRC-II benchmarks at both hourly and shift-level granularity and on 36 synthetic configurations.
发表机构
- Phi Labs, Quantiphi（Phi Labs，Quantiphi）
机构由 AI 辅助整理，请以论文原文为准。
