Lagrangian Core

Augmented Lagrangian for constrained optimization. Handles convex QP, smooth NLP, non-convex NLP, distributed ADMM. Trigger on: constrained optimization, KKT, Lagrange multipliers, ALM, ADMM, multi-start, penalty methods.

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Lagrangian Core Skill — v0.3.0

能力边界

支持: 凸QP | 光滑NLP | 非凸NLP(multi-start) | 分布式ADMM 不支持: Safe RL | 多目标 | 贝叶斯混合

方法路由

convex_qp/smooth_nlp → standard_solver
non_convex           → ALM(n_starts=5, uniform_random)
distributed          → ADMM

Step 3 — 稀疏JSON通道

{"step":3,"type":"augmented_lagrangian",
 "formula":"L_ρ=f(x)+Σλ·h(x)+Σμ·g(x)+ρ/2·||h||²",
 "multipliers":{"lambda":[0.0],"mu":[0.0]},
 "penalty":{"rho_init":1.0,"update_rule":"×1.5 if ||h||>tol"}}

Step 4 — KKT验证

缓存指纹=(变量数, eq约束数, ineq约束数, 目标函数类型)

Step 7 — 输出

最优解(一行) → 约束状态 → KKT残差

Forbidden Behaviors

❌ Steps 1-6输出自然语言 ❌ 失败后输出散文

Sliky1/lagrangian-skills/tree/main/archive/v0.3.0 commit ec029f1254

Frequently asked questions

npx skillmds@latest add sliky1/lagrangian-core-2