让采购与库存计划自动遵守合同条款,避免因遗漏或错误导致违规。
Contract2Plan: Verified Contract-Grounded Retrieval-Augmented Optimization for BOM-Aware Procurement and Multi-Echelon Inventory Planning
- 用检索+提取构建带证据的约束模型,再交由求解器验证合规性
- 实验显示纯提取方法在500个案例中出现严重违约和计划不可行
- 对可修复条款自动修复,不可靠时主动放弃,适合高风险供应链系统
采购与库存规划不仅依赖需求预测和物料清单(BOM),还受合同与供应商文件中的运营条款(如最小订购量、交货周期、价格阶梯、分配上限、替代批准等)约束。基于大模型的条款提取虽能加速结构化,但仅靠提取或纯大模型决策易出错:遗漏条款、单位错误、冲突未解,可能导致不可行计划或隐性合同违约,且在BOM耦合下问题被放大。我们提出Contract2Plan,一种从生成式AI到优化器的可验证管道,在输出计划前加入基于求解器的合规校验环节。系统通过溯源检索条款证据,提取带证据范围的类型化约束模式,将约束编译为考虑BOM的混合整数线性规划(MILP),并利用求解器诊断验证其接地性、资格、一致性与可行性,发现异常时触发定向修复或拒绝执行。我们形式化了哪些条款类别可进行保守修复并保证合同安全可行性,哪些需人工确认。一个自包含的合成微型基准(500实例;T=5)在含最小订购量提升和紧急采购的执行模型下精确枚举得出,表明提取独立试验存在重尾后悔值和显著的最小订购量违约率,凸显验证作为合同驱动规划系统核心组件的必要性。
原文摘要 · Abstract (English)
Procurement and inventory planning is governed not only by demand forecasts and bills of materials (BOMs), but also by operational terms in contracts and supplier documents (e.g., MOQs, lead times, price tiers, allocation caps, substitution approvals). LLM-based extraction can speed up structuring these terms, but extraction-only or LLM-only decision pipelines are brittle: missed clauses, unit errors, and unresolved conflicts can yield infeasible plans or silent contract violations, amplified by BOM coupling. We introduce Contract2Plan, a verified GenAI-to-optimizer pipeline that inserts a solver-based compliance gate before plans are emitted. The system retrieves clause evidence with provenance, extracts a typed constraint schema with evidence spans, compiles constraints into a BOM-aware MILP, and verifies grounding, eligibility, consistency, and feasibility using solver diagnostics, triggering targeted repair or abstention when automation is unsafe. We formalize which clause classes admit conservative repair with contract-safe feasibility guarantees and which require human confirmation. A self-contained synthetic micro-benchmark (500 instances; T=5) computed by exact enumeration under an execution model with MOQ uplift and emergency purchases shows heavy-tailed regret and nontrivial MOQ-violation incidence for extraction-only planning, motivating verification as a first-class component of contract-grounded planning systems.
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