278 lines
11 KiB
Plaintext
278 lines
11 KiB
Plaintext
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# ============================================================
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# 主控参数敏感性分析（moduleId: domain-sensitivity, SC-06，可重生 ✅）
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# 沙盒 one-at-a-time 扰动 + 固定种子蒙特卡洛；永不写主干
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# ============================================================
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from __future__ import annotations
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import copy
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import uuid
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from typing import Any
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from server.aps_domain.params import get_schedule_params
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from server.aps_domain.robustness import run_monte_carlo
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from server.contracts import UIBlock
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from server.engines import get_engine
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from server.engines.base import EngineParams
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from server.timeutil import add_minutes, fmt_date, today0
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World = dict[str, Any]
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def _sandbox_counter():
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counters: dict[str, int] = {}
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def next_id(kind: str) -> int:
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counters[kind] = counters.get(kind, 0) + 2000000
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return counters[kind]
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return next_id
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def _kpi_from_result(result, sandbox: World) -> dict[str, float]:
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ver = sandbox["scheduleVersions"][-1] if sandbox.get("scheduleVersions") else {}
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return {
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"tardiness": round(float(result.totalTardiness), 2),
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"conflicts": float(result.conflictCount),
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"utilization": round(float(result.avgUtilization), 4),
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"changeoverMin": float(ver.get("totalChangeoverMin") or 0),
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"poCount": float(result.poCount),
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"woCount": float(result.woCount),
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}
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def _run_sandbox(
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world: World,
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*,
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strategy: str,
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horizon: int,
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start: str,
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vip_weight: float | None = None,
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delivery_buffer: float | None = None,
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freeze_hours: float | None = None,
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efficiency_scale: float | None = None,
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) -> dict[str, float]:
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sandbox = copy.deepcopy(world)
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sandbox["scheduleVersions"] = []
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sandbox["productionOrders"] = [p for p in sandbox.get("productionOrders", []) if p.get("status") == "PUBLISHED"]
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sandbox["workOrders"] = [w for w in sandbox.get("workOrders", []) if w.get("status") not in ("PENDING", "DRAFT", None)]
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# 清空草稿工单/PO，避免干扰；简化：只保留非本沙盒相关——种子通常无已发布，直接清空排产结果
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sandbox["productionOrders"] = []
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sandbox["workOrders"] = []
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sandbox["conflicts"] = []
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sp = sandbox.setdefault("scheduleParams", {})
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if vip_weight is not None:
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levels = dict(sp.get("customerLevelWeights") or {})
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levels["VIP"] = float(vip_weight)
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sp["customerLevelWeights"] = levels
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if efficiency_scale is not None and efficiency_scale > 0:
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for ln in sandbox.get("lines") or []:
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base = float(ln.get("efficiencyFactor") or 1.0)
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ln["efficiencyFactor"] = round(base * float(efficiency_scale), 4)
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params = EngineParams(
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orderIds=[],
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engineType="RULE",
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strategyTemplate=strategy,
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planningHorizonDays=horizon,
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startDate=start,
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deliveryBufferRatio=delivery_buffer,
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freezeWindowHours=freeze_hours,
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name=f"sensitivity-{uuid.uuid4().hex[:6]}",
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constraints={
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"materialKit": False, "equipment": True, "personnel": True, "changeover": True,
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"capacity": True, "dueDate": True, "tooling": True, "freeze": True,
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},
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)
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result = get_engine("RULE").solve(sandbox, params, _sandbox_counter())
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return _kpi_from_result(result, sandbox)
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def run_sensitivity(
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world: World,
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*,
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strategy: str = "COMPREHENSIVE",
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) -> dict[str, Any]:
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"""
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SC-06：Tornado 单因子排序 + 固定种子蒙特卡洛鲁棒性。
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经统一 Explore 通道执行（矩阵 55 行）：fn 只拿深拷贝沙盒，主干永不外泄写引用；
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_run_sandbox 内部再做子沙盒扰动。
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"""
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from server.aps_domain.explore_boundary import run_explore
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return run_explore(world, lambda sandbox: _sensitivity_impl(
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sandbox, strategy=strategy,
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))
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def _sensitivity_impl(world: World, *, strategy: str) -> dict[str, Any]:
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"""Tornado/蒙特卡洛核心实现（在统一通道沙盒内运行）。"""
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sp = get_schedule_params(world)
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base_horizon = int(sp.get("planningHorizonDays") or 14)
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base_vip = float((sp.get("customerLevelWeights") or {}).get("VIP") or 3.0)
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base_buffer = float(sp.get("deliveryBufferRatio") or 0.95)
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base_freeze = float(sp.get("freezeWindowHours") or 24)
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start = fmt_date(add_minutes(today0(), 24 * 60))
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baseline = _run_sandbox(
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world, strategy=strategy, horizon=base_horizon, start=start,
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vip_weight=base_vip, delivery_buffer=base_buffer, freeze_hours=base_freeze,
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efficiency_scale=1.0,
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)
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# 每因子：低/高 两档（相对基线）
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factors: list[dict[str, Any]] = [
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{
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"id": "planningHorizonDays", "label": "展望期(天)",
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"baseline": base_horizon,
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"low": {"label": f"{max(3, base_horizon // 2)} 天", "kwargs": {"horizon": max(3, base_horizon // 2)}},
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"high": {"label": f"{min(60, base_horizon * 2)} 天", "kwargs": {"horizon": min(60, base_horizon * 2)}},
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},
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{
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"id": "vipWeight", "label": "VIP 等级权重",
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"baseline": base_vip,
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"low": {"label": "VIP=1", "kwargs": {"vip_weight": 1.0}},
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"high": {"label": "VIP=10", "kwargs": {"vip_weight": 10.0}},
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},
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{
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"id": "deliveryBufferRatio", "label": "交期缓冲比",
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"baseline": base_buffer,
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"low": {"label": "缓冲 0.85", "kwargs": {"delivery_buffer": 0.85}},
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"high": {"label": "缓冲 1.00", "kwargs": {"delivery_buffer": 1.0}},
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},
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{
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"id": "freezeWindowHours", "label": "冻结窗口(时)",
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"baseline": base_freeze,
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"low": {"label": "冻结 0h", "kwargs": {"freeze_hours": 0.0}},
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"high": {"label": "冻结 48h", "kwargs": {"freeze_hours": 48.0}},
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},
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{
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"id": "lineEfficiency", "label": "产线效率系数",
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"baseline": 1.0,
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"low": {"label": "效率×0.8", "kwargs": {"efficiency_scale": 0.8}},
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"high": {"label": "效率×1.2", "kwargs": {"efficiency_scale": 1.2}},
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},
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]
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rows: list[dict[str, Any]] = []
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for fac in factors:
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common = {
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"strategy": strategy, "horizon": base_horizon, "start": start,
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"vip_weight": base_vip, "delivery_buffer": base_buffer,
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"freeze_hours": base_freeze, "efficiency_scale": 1.0,
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}
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low_kw = {**common, **fac["low"]["kwargs"]}
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high_kw = {**common, **fac["high"]["kwargs"]}
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# kwargs 用 horizon 键
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def _call(kw: dict) -> dict[str, float]:
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return _run_sandbox(
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world,
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strategy=kw["strategy"],
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horizon=int(kw["horizon"]),
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start=kw["start"],
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vip_weight=kw.get("vip_weight"),
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delivery_buffer=kw.get("delivery_buffer"),
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freeze_hours=kw.get("freeze_hours"),
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efficiency_scale=kw.get("efficiency_scale"),
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)
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low_kpi = _call(low_kw)
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high_kpi = _call(high_kw)
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d_low = round(low_kpi["tardiness"] - baseline["tardiness"], 2)
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d_high = round(high_kpi["tardiness"] - baseline["tardiness"], 2)
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rows.append({
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"factorId": fac["id"],
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"label": fac["label"],
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"baselineValue": fac["baseline"],
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"lowLabel": fac["low"]["label"],
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"highLabel": fac["high"]["label"],
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"low": {
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"tardiness": low_kpi["tardiness"],
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"conflicts": low_kpi["conflicts"],
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"utilization": low_kpi["utilization"],
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"deltaTardiness": d_low,
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"deltaConflicts": round(low_kpi["conflicts"] - baseline["conflicts"], 1),
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},
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"high": {
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"tardiness": high_kpi["tardiness"],
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"conflicts": high_kpi["conflicts"],
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"utilization": high_kpi["utilization"],
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"deltaTardiness": d_high,
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"deltaConflicts": round(high_kpi["conflicts"] - baseline["conflicts"], 1),
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},
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"swing": round(abs(d_low) + abs(d_high), 2),
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"impactMetric": "tardiness",
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})
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rows.sort(key=lambda r: r["swing"], reverse=True)
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monte_carlo = run_monte_carlo(
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world,
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strategy=strategy,
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engine_type="RULE",
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baseline_kpi=baseline,
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planning_horizon_days=base_horizon,
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start_date=start,
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delivery_buffer_ratio=base_buffer,
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freeze_window_hours=base_freeze,
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constraints={
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"materialKit": False, "equipment": True, "personnel": True, "changeover": True,
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"capacity": True, "dueDate": True, "tooling": True, "freeze": True,
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},
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reset_schedule_products=True,
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)
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md_lines = [
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"# 敏感性分析（Tornado）",
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"",
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f"- 策略基线：`{strategy}`",
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f"- 基线 KPI：延期 **{baseline['tardiness']}** h · 冲突 **{int(baseline['conflicts'])}** · "
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f"利用率 **{round(baseline['utilization'] * 100, 1)}%** · 换型 **{baseline['changeoverMin']}** 分",
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"- 说明：沙盒 one-at-a-time，不写主干；超时秒数对 RULE 无意义，未纳入。",
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"",
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"| 因子 | 低档 Δ延期 | 高档 Δ延期 | 摆幅 |",
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"| --- | ---: | ---: | ---: |",
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]
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for r in rows:
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md_lines.append(
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f"| {r['label']}（{r['lowLabel']} / {r['highLabel']}） | "
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f"{r['low']['deltaTardiness']:+} | {r['high']['deltaTardiness']:+} | {r['swing']} |"
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)
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md_lines.append("")
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md_lines.append("摆幅 = |低档Δ延期| + |高档Δ延期|；越大表示该参数对延期越敏感。")
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md_lines.extend([
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"",
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"## 固定种子蒙特卡洛鲁棒性",
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"",
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f"- 种子：`{monte_carlo['seed']}` · 样本：**{monte_carlo['trials']}** 次",
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f"- 鲁棒性：**{round(monte_carlo['robustness'] * 100, 1)}%**",
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f"- 延期分布：P50 **{monte_carlo['distribution']['tardinessP50']}h** · "
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f"P90 **{monte_carlo['distribution']['tardinessP90']}h**",
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])
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return {
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"strategy": strategy,
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"baseline": baseline,
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"rows": rows,
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"monteCarlo": monte_carlo,
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"markdown": "\n".join(md_lines),
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"hint": "敏感性只跑沙盒。若要固化参数，请到设置 → 排产参数 改权重/展望期并确认（P2）。",
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}
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def sensitivity_as_block(report: dict[str, Any]) -> UIBlock:
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"""产出 report UI 块（可预览/下载）。"""
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return UIBlock(
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blockId=f"sensitivity-{uuid.uuid4().hex[:8]}",
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type="report",
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props={
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"reportId": uuid.uuid4().hex[:10],
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"title": f"敏感性分析 Tornado（{report.get('strategy')}）",
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"markdown": report.get("markdown") or "",
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"reportType": "sensitivity-tornado",
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"baseline": report.get("baseline"),
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"rows": report.get("rows"),
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"monteCarlo": report.get("monteCarlo"),
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},
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)
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