接入 Optimize 柔性 V2 闭环

新增 Python OptimizeEngine 和七种派工规则，复用 APS 能力池与物化逻辑。

通过 flex.schedule 的 engine=OPTIMIZE 进入闭环 V2，记录 solver、algorithm、provenance，并在准入阻断时保留引擎身份且不产生工单。

新增 Optimize/V2/注册表黄金测试；CP-SAT 原生 V2 求解与真实 MOM world 留待后续环境和轮次验证。

apps/web/src/api/types.ts

@@ -197,7 +197,7 @@ export interface IntentResult {
   source: 'RULE_FAST' | 'LLM';                        // 产生来源
 }
 
-export type ScheduleEngineType = 'RULE' | 'CP' | 'GA' | 'HYBRID' | 'EXTERNAL';
+export type ScheduleEngineType = 'RULE' | 'CP' | 'GA' | 'HYBRID' | 'EXTERNAL' | 'OPTIMIZE';
 
 export interface ScheduleResult {
   versionId: number;

docs/round-85-optimize-integration-shape-plan.md

@@ -183,6 +183,15 @@ optimize 只能产生候选排产解。Harness、Workflow、WorldStore、版本
 
 PLAN AUDIT: PASS
 
+## 14. 本轮实施结果
+
+- 已新增 `server/engines/optimize_engine.py`，并通过 `get_engine("OPTIMIZE")` 接入 APS。
+- 七种派工规则（EDD/SPT/PRIORITY/FIFO/LPT/CR/ATC）共用 APS 的能力池、日历、班组、工装和物化逻辑；结果统一进入 `SchedulingSolutionV2` 校验。
+- `/api/flex/schedule` 增加 `engine=OPTIMIZE`；Optimize 版本记录 `solverId`、`solverVersion`、`algorithmId`、`algorithmVersion`，并保留 V2 provenance 和 adapter assumption。
+- 准入阻断时仍由 APS 记录零工单 DRAFT 版本，同时保留请求的引擎身份和 blocker，不绕过 admission。
+- 新增 `tests/golden/test_optimize_engine.py`；Optimize/V2/算法注册表相关定向测试共 20 项通过，相关 APS 回归共 34 项通过。
+- 当前 APS 轮次工作树未包含 `server/data/world-proj_712276ba.json`，因此真实 MOM world 用例只能按既有测试策略跳过；全量 CP/Excel 测试还受到当前环境 NumPy（X86_V2）二进制不兼容影响。CP-SAT 的 V2 原生求解器仍应作为后续轮次接入，本轮不把 PoolEngine 适配器冒充为 CP-SAT 最优证明。
+
 阻塞问题：无。
 
 检查结论：目标、写入范围、验收标准、验证命令、真实 MOM 门禁和停止条件均已明确；单 agent 任务没有并行写入冲突，也没有依赖未讨论的产品决策。
@@ -197,4 +206,3 @@ PLAN AUDIT: PASS
 - 用户确认后才能进入目标模式实现；当前不修改生产代码。
 - 实现完成后必须通过自身检查；如形成集成结果，补充统一集成审计和真实 MOM 验证。
 - 轮次结束时保留计划、验证证据和未合并分支，直到用户明确决定是否合并。
-

server/agent_core/algolib.py

@@ -120,6 +120,63 @@ def _builtin_catalog() -> list[AlgorithmManifest]:
         "constraints": "dict<bool 约束开关>",
     }
     items = [
+        # ---- A. Optimize Python-native dispatch rules ----
+        AlgorithmManifest(
+            algo_id="optimize.edd", name="Optimize EDD 最早交期",
+            category="A", description="Optimize V2 适配器：按最早交期派工",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:EDD", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.spt", name="Optimize SPT 最短工时",
+            category="A", description="Optimize V2 适配器：短工时优先",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:SPT", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.priority", name="Optimize PRIORITY 优先级",
+            category="A", description="Optimize V2 适配器：订单优先级优先",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:PRIORITY", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.fifo", name="Optimize FIFO 先来先服务",
+            category="A", description="Optimize V2 适配器：按释放时间派工",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:FIFO", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.lpt", name="Optimize LPT 最长工时",
+            category="A", description="Optimize V2 适配器：长工时优先",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:LPT", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.cr", name="Optimize CR 临界比",
+            category="A", description="Optimize V2 适配器：交期紧迫度优先",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:CR", regen_strategy="manual",
+        ),
+        AlgorithmManifest(
+            algo_id="optimize.atc", name="Optimize ATC 逾期成本",
+            category="A", description="Optimize V2 适配器：逾期成本代理排序",
+            scale_limit="<=50k 工单", time_budget="毫秒级",
+            input_schema=rule_in, output_schema=kpi_out,
+            golden_tests=["tests/golden/test_optimize_engine.py"], deterministic=True,
+            entrypoint="OPTIMIZE:ATC", regen_strategy="manual",
+        ),
         # ---- A. 启发式（RULE 引擎各策略模板）----
         AlgorithmManifest(
             algo_id="rule.delivery_first", name="EDD 最早交期",
@@ -436,10 +493,10 @@ class AlgorithmRegistry:
         """入口可达性：引擎名 / ENGINE:STRATEGY / module.path:attr。"""
         if ":" not in entrypoint:
             return True, ""                             # 纯引擎名（RULE/CP/GA/HYBRID）由 get_engine 工厂保证
-        if entrypoint.startswith("RULE:"):
+        if entrypoint.startswith(("RULE:", "OPTIMIZE:")):
             from server.engines import get_engine
             try:
-                get_engine("RULE")
+                get_engine(entrypoint.split(":", 1)[0])
                 return True, ""
             except (ImportError, AttributeError, RuntimeError, ValueError, TypeError) as exc:
                 return False, str(exc)

server/aps_domain/closed_loop_runtime.py

@@ -43,6 +43,7 @@ from server.aps_domain.scheduling_problem_v2 import (
 )
 from server.aps_domain.scheduling_validator import validate_solution
 from server.engines.pool_engine import PoolEngine
+from server.engines.optimize_engine import OptimizeEngine
 
 World = dict[str, Any]
 _TZ = ZoneInfo("Asia/Shanghai")
@@ -624,7 +625,13 @@ def persist_closed_loop_projection(world: World, closed_loop: ClosedLoopProblem,
     }
 
 
-def record_blocked_flex_version(world: World, next_id, closed_loop: ClosedLoopProblem) -> dict[str, Any]:
+def record_blocked_flex_version(
+    world: World,
+    next_id,
+    closed_loop: ClosedLoopProblem,
+    *,
+    engine_type: str = "CLOSED_LOOP",
+) -> dict[str, Any]:
     """Record an honest zero-WO DRAFT version when manufacturing admission is blocked."""
 
     world.setdefault("flexScheduleVersions", [])
@@ -632,13 +639,18 @@ def record_blocked_flex_version(world: World, next_id, closed_loop: ClosedLoopPr
     world.setdefault("flexWorkOrders", [])
     world.setdefault("flexConflicts", [])
     version_id = next_id("flexScheduleVersion")
+    normalized_engine = (
+        "OPTIMIZE"
+        if str(engine_type or "CLOSED_LOOP").strip().upper() == "OPTIMIZE"
+        else "CLOSED_LOOP"
+    )
     version_no = f"FV{closed_loop.business_date.replace('-', '')}-{len(world['flexScheduleVersions']) + 1:03d}"
     version = {
         "id": version_id,
         "versionNo": version_no,
         "versionName": f"闭环排产准入阻断 {closed_loop.business_date}",
         "sortMode": "CLOSED_LOOP",
-        "engineType": "CLOSED_LOOP",
+        "engineType": normalized_engine,
         "status": "DRAFT",
         "solveStatus": "BLOCKED",
         "planningProblemId": closed_loop.problem_id,
@@ -682,7 +694,7 @@ def record_blocked_flex_version(world: World, next_id, closed_loop: ClosedLoopPr
     return {
         "versionId": version_id,
         "versionNo": version_no,
-        "engineType": "CLOSED_LOOP",
+        "engineType": normalized_engine,
         "status": "DRAFT",
         "solveStatus": "BLOCKED",
         "orderCount": version["orderCount"],
@@ -1003,15 +1015,19 @@ def flex_version_to_solution_v2(
         unscheduledRequirements=unscheduled,
         hardViolations=hard_conflicts,
         assumptions=(Assumption(
-            code="POOL_ENGINE_V1_ADAPTER",
+            code=("OPTIMIZE_ENGINE_V1_ADAPTER"
-            message="PoolEngine 候选结果已映射到闭环 V2 契约并执行独立校验",
+                  if str(version.get("engineType") or "").upper() == "OPTIMIZE"
+                  else "POOL_ENGINE_V1_ADAPTER"),
+            message=("OptimizeEngine 候选结果已映射到闭环 V2 契约并执行独立校验"
+                     if str(version.get("engineType") or "").upper() == "OPTIMIZE"
+                     else "PoolEngine 候选结果已映射到闭环 V2 契约并执行独立校验"),
             sourceRef=f"flex-version:{version_id}",
             confidence=1.0,
         ),),
         provenance=SolutionProvenance(
             runId=f"flex-version:{version_id}",
-            solverId="pool-engine",
+            solverId=str(version.get("solverId") or "pool-engine"),
-            solverVersion="closed-loop-v1",
+            solverVersion=str(version.get("solverVersion") or "closed-loop-v1"),
             generatedAt=generated_at,
             businessDate=business_day,
             problemHash=scheduling_problem_hash(problem),
@@ -1104,6 +1120,7 @@ def run_closed_loop_candidate(
     sort_mode: str | None = None,
     window: str | None = None,
     name: str | None = None,
+    engine_type: str = "CLOSED_LOOP",
     strict: bool = True,
 ) -> dict[str, Any]:
     """Build, solve and validate one closed-loop candidate with version-level atomicity."""
@@ -1134,7 +1151,12 @@ def run_closed_loop_candidate(
         }
     }
     if not admitted:
-        result = record_blocked_flex_version(world, next_id, closed_loop)
+        result = record_blocked_flex_version(
+            world,
+            next_id,
+            closed_loop,
+            engine_type=engine_type or "CLOSED_LOOP",
+        )
         return {**result, **base, "validation": None}
 
     candidate = deepcopy(world)
@@ -1146,6 +1168,22 @@ def run_closed_loop_candidate(
         candidate.setdefault(key, [] if key != "flexParams" else {})
     projected = project_admitted_demands_to_flex_orders(candidate, closed_loop)
     schedule_start = schedule_start_date or (_as_day(business_date) + timedelta(days=1)).isoformat()
+    normalized_engine = (
+        "OPTIMIZE"
+        if str(engine_type or "CLOSED_LOOP").strip().upper() == "OPTIMIZE"
+        else "CLOSED_LOOP"
+    )
+    if normalized_engine == "OPTIMIZE":
+        solved = OptimizeEngine().solve_flex(
+            candidate,
+            next_id,
+            dispatch_rule=sort_mode,
+            order_ids=projected["orderIds"],
+            start_date=schedule_start,
+            name=name or f"Optimize 闭环排产 {business_date}",
+            window=window,
+        )
+    else:
         solved = PoolEngine().solve(
             candidate,
             next_id,
@@ -1159,7 +1197,11 @@ def run_closed_loop_candidate(
     version = next(row for row in candidate["flexScheduleVersions"] if row.get("id") == version_id)
     version["versionNo"] = f"FV{business_date.replace('-', '')}-{len(candidate['flexScheduleVersions']):03d}"
     version["versionName"] = name or f"闭环排产 {business_date}"
-    version["engineType"] = "CLOSED_LOOP"
+    version["engineType"] = normalized_engine
+    version["solverId"] = str(solved.get("solverId") or ("pool-engine" if normalized_engine != "OPTIMIZE" else "optimize-dispatch"))
+    version["solverVersion"] = str(solved.get("solverVersion") or ("closed-loop-v1" if normalized_engine != "OPTIMIZE" else "1.0.0"))
+    version["algorithmId"] = solved.get("algorithmId")
+    version["algorithmVersion"] = solved.get("algorithmVersion")
     version["planningProblemId"] = closed_loop.problem_id
     version["planningSourceHash"] = closed_loop.source_revision
     version["demandCount"] = len(closed_loop.manufacturing_demands)
@@ -1167,7 +1209,7 @@ def run_closed_loop_candidate(
     version["unscheduledDemandCount"] = max(0, len(admitted) - int(version.get("vlCount") or 0))
     version["createdAt"] = f"{business_date} 00:00"
     solved["versionNo"] = version["versionNo"]
-    solved["engineType"] = "CLOSED_LOOP"
+    solved["engineType"] = normalized_engine
 
     solution = flex_version_to_solution_v2(candidate, closed_loop, problem, version_id)
     report = validate_solution(problem, solution, world=candidate)

server/aps_domain/flex.py

@@ -233,7 +233,8 @@ def run_flex_schedule(store, sort_mode: str | None = None, order_ids: list[int]
                       start_date: str | None = None, name: str | None = None,
                       actor: str = "web", window: str | None = None,
                       enforce_teams: bool | None = None,
-                      trial: bool = False) -> dict:
+                      trial: bool = False,
+                      engine_type: str | None = None) -> dict:
     """Run the governed closed-loop scheduling pipeline as one P1 action.
 
     Real/site worlds always use the closed-loop requirement, supply, routing and
@@ -300,9 +301,14 @@ def run_flex_schedule(store, sort_mode: str | None = None, order_ids: list[int]
                 sort_mode=sort_mode,
                 window=window,
                 name=name,
+                engine_type=engine_type or "CLOSED_LOOP",
                 strict=True,
             )
-            result["executionMode"] = "CLOSED_LOOP_V1"
+            result["executionMode"] = (
+                "OPTIMIZE_CLOSED_LOOP_V1"
+                if str(engine_type or "").upper() == "OPTIMIZE"
+                else "CLOSED_LOOP_V1"
+            )
         result["salesOrdersSynced"] = synced
         result["decompose"] = {
             "orders": len(decomposition.get("orders") or []),

server/aps_domain/params.py

@@ -96,8 +96,8 @@ def normalize_params_payload(payload: dict[str, Any]) -> dict[str, Any]:
 
     if "defaultEngine" in payload and payload["defaultEngine"] is not None:
         eng = str(payload["defaultEngine"]).upper()
-        if eng not in ("RULE", "CP", "GA", "HYBRID"):
+        if eng not in ("RULE", "CP", "GA", "HYBRID", "OPTIMIZE"):
-            raise ValueError("defaultEngine 须为 RULE/CP/GA/HYBRID")
+            raise ValueError("defaultEngine 须为 RULE/CP/GA/HYBRID/OPTIMIZE")
         out["defaultEngine"] = eng
 
     if "cpTimeLimitSeconds" in payload and payload["cpTimeLimitSeconds"] is not None:

server/aps_domain/workflow.py

@@ -151,6 +151,10 @@ def _run_schedule(store: WorldStore, intent: IntentResult, actor: str) -> AgentR
         constraints=engine_constraint_flags(store.data),           # SC-04 约束剖面 → 引擎开关
         timeLimitSeconds=float(sp["cpTimeLimitSeconds"]) if sp.get("cpTimeLimitSeconds") is not None else 8.0,
     )
+    if params.engineType == "OPTIMIZE":
+        return AgentReply(
+            text="Optimize 目前只支持柔性 V2 闭环，请通过 /api/flex/schedule 并指定 engine=OPTIMIZE。"
+        )
     engine = get_engine(params.engineType)             # CP / HYBRID 真管线；GA 仍 RULE 代跑
     result: ScheduleResult = engine.solve(store.data, params, store.next_id)  # 求解（写内存世界）
     # 可追溯链：run-id / 算法版本 / 种子 / 知识版本 / 用户确认 串成一条链（§8.4）

server/contracts.py

@@ -125,7 +125,7 @@ class ScheduleResult(BaseModel):
     """排产结果摘要：引擎 solve() 的标准输出（§9.1），回复/审计/KPI 共用。"""
     versionId: int                                     # 版本 ID
     versionNo: str                                     # 版本号（V+日期+序号）
-    engineType: Literal["RULE", "CP", "GA", "HYBRID", "EXTERNAL"]  # 引擎类型
+    engineType: Literal["RULE", "CP", "GA", "HYBRID", "EXTERNAL", "OPTIMIZE"]  # 引擎类型
     strategy: str                                      # 策略模板
     status: Literal["DRAFT", "PUBLISHED", "ARCHIVED"] = "DRAFT"  # 版本状态
     orderCount: int                                    # 参与排产的订单项数

server/engines/__init__.py

@@ -8,6 +8,7 @@ from server.engines.cp_engine import CpSatEngine, HybridEngine
 from server.engines.external_engine import ExternalEngine
 from server.engines.ga_engine import GeneticAlgorithmEngine
 from server.engines.nsga2_engine import NSGA2Engine, nsga2_defaults, solve_nsga2
+from server.engines.optimize_engine import OptimizeEngine
 from server.engines.pool_engine import PoolEngine
 from server.engines.rule_engine import RuleEngine
 
@@ -19,6 +20,7 @@ __all__ = [
     "HybridEngine",
     "ISchedulingEngine",
     "NSGA2Engine",
+    "OptimizeEngine",
     "PoolEngine",
     "RuleEngine",
     "get_engine",
@@ -28,7 +30,7 @@ __all__ = [
 
 
 def get_engine(engine_type: str) -> ISchedulingEngine:
-    """引擎工厂：RULE / CP / GA / HYBRID / NSGA2 / EXTERNAL。"""
+    """引擎工厂：RULE / CP / GA / HYBRID / NSGA2 / OPTIMIZE / EXTERNAL。"""
     kind = (engine_type or "RULE").upper()
     if kind.startswith("EXTERNAL"):
         skill_id = None
@@ -43,4 +45,6 @@ def get_engine(engine_type: str) -> ISchedulingEngine:
         return GeneticAlgorithmEngine()
     if kind == "NSGA2":
         return NSGA2Engine()
+    if kind == "OPTIMIZE":
+        return OptimizeEngine()
     return RuleEngine(requested_type="RULE")

server/engines/base.py

@@ -14,7 +14,7 @@ from server.contracts import ScheduleResult            # 引擎输出契约
 class EngineParams(BaseModel):
     """引擎入参：一次排产请求的全部参数（与 legacy runScheduling params 对齐）。"""
     orderIds: list[int] = Field(default_factory=list)  # 目标订单 ID（空=全部待排）
-    engineType: str = "RULE"                           # 请求的引擎类型（RULE/CP/GA/HYBRID）
+    engineType: str = "RULE"                           # 请求的引擎类型（RULE/CP/GA/HYBRID/OPTIMIZE）
     strategyTemplate: str = "COMPREHENSIVE"            # 策略模板（排序规则）
     planningHorizonDays: int = 14                      # 计划展望期（天）
     startDate: str | None = None                       # 排产起始日 YYYY-MM-DD（None=明天）

server/engines/optimize_engine.py

@@ -0,0 +1,115 @@
+"""Optimize scheduling engine integrated with the APS V2 closed loop.
+
+The engine owns algorithm selection and provenance. APS still owns the world,
+admission, candidate validation, version materialization, and audit trail.
+"""
+from __future__ import annotations
+
+from typing import Any, Callable
+
+from server.contracts import ScheduleResult
+from server.engines.base import EngineParams, ISchedulingEngine
+from server.engines.pool_engine import PoolEngine
+
+
+DISPATCH_RULES = frozenset({"EDD", "SPT", "PRIORITY", "FIFO", "LPT", "CR", "ATC"})
+
+
+def normalize_dispatch_rule(value: str | None) -> str:
+    rule = str(value or "EDD").strip().upper().replace("-", "_")
+    aliases = {
+        "DELIVERY_FIRST": "EDD",
+        "EARLIEST_DUE_DATE": "EDD",
+        "FIRST_IN_FIRST_OUT": "FIFO",
+        "APPARENT_TARDINESS_COST": "ATC",
+    }
+    rule = aliases.get(rule, rule)
+    return rule if rule in DISPATCH_RULES else "EDD"
+
+
+class OptimizeEngine(ISchedulingEngine):
+    """Python-native Optimize entry point for APS scheduling.
+
+    The first integration reuses PoolEngine's already validated flex
+    materializer. Its ordering policy is supplied by ``dispatch_rule`` so the
+    seven optimize rules share APS calendars, teams, tooling, and rollback
+    semantics while the V2 runtime remains the authority for validation.
+    """
+
+    name = "OPTIMIZE"
+    supports_anytime = False
+
+    def solve(
+        self,
+        world: dict[str, Any],
+        params: EngineParams,
+        next_id: Callable[[str], int],
+    ) -> ScheduleResult:
+        rule = normalize_dispatch_rule(params.strategyTemplate)
+        solved = PoolEngine().solve(
+            world,
+            next_id,
+            sort_mode="ASC",
+            order_ids=params.orderIds or None,
+            start_date=params.startDate,
+            name=params.name,
+            window=None,
+            enforce_teams=params.constraints.get("personnel") if params.constraints else None,
+            dispatch_rule=rule,
+        )
+        return _summary_to_result(solved, rule)
+
+    def solve_flex(
+        self,
+        world: dict[str, Any],
+        next_id: Callable[[str], int],
+        *,
+        dispatch_rule: str | None = None,
+        order_ids: list[int] | None = None,
+        start_date: str | None = None,
+        name: str | None = None,
+        window: str | None = None,
+        enforce_teams: bool | None = None,
+    ) -> dict[str, Any]:
+        """Materialize an Optimize candidate for the closed-loop V2 adapter."""
+
+        rule = normalize_dispatch_rule(dispatch_rule)
+        solved = PoolEngine().solve(
+            world,
+            next_id,
+            sort_mode="ASC",
+            order_ids=order_ids,
+            start_date=start_date,
+            name=name,
+            window=window,
+            enforce_teams=enforce_teams,
+            dispatch_rule=rule,
+        )
+        solved.update({
+            "engineType": "OPTIMIZE",
+            "algorithmId": f"optimize.{rule.lower()}",
+            "algorithmVersion": "1.0.0",
+            "solverId": "optimize-dispatch",
+            "solverVersion": "1.0.0",
+            "dispatchRule": rule,
+        })
+        return solved
+
+
+def _summary_to_result(solved: dict[str, Any], rule: str) -> ScheduleResult:
+    return ScheduleResult(
+        versionId=int(solved["versionId"]),
+        versionNo=str(solved["versionNo"]),
+        engineType="OPTIMIZE",
+        strategy=rule,
+        status="DRAFT",
+        orderCount=int(solved.get("orderCount") or 0),
+        poCount=int(solved.get("vlCount") or 0),
+        woCount=int(solved.get("woCount") or 0),
+        conflictCount=int(solved.get("conflictCount") or 0),
+        totalTardiness=float(solved.get("totalTardiness") or 0),
+        avgUtilization=float(solved.get("avgUtilization") or 0),
+        evidenceRefs=[f"algorithm:optimize.{rule.lower()}", f"run:{solved['versionId']}"],
+        solveStatus="FEASIBLE" if not solved.get("conflictCount") else "PARTIAL",
+    )
+

server/engines/pool_engine.py

@@ -97,7 +97,8 @@ class PoolEngine:
               start_date: str | None = None, name: str | None = None,
               window: str | None = None,
               seed_busy: dict[int, list[tuple[datetime, datetime]]] | None = None,
-              enforce_teams: bool | None = None) -> dict[str, Any]:
+              enforce_teams: bool | None = None,
+              dispatch_rule: str | None = None) -> dict[str, Any]:
         """执行一次柔性排产，返回结果摘要 dict。
 
         Args:
@@ -148,7 +149,10 @@ class PoolEngine:
             orders.append(o)
 
         # ---- ③ 派工排序（吸收排产逻辑 PPT：正排 EDD / 倒排最晚优先 / 瓶颈锚）----
-        if mode == SORT_DESC:
+        dispatch = str(dispatch_rule or "").strip().upper()
+        if dispatch in {"SPT", "LPT", "CR", "ATC", "PRIORITY", "FIFO", "EDD"}:
+            orders.sort(key=lambda o: self._dispatch_key(dispatch, o, routings, ops_by_code))
+        elif mode == SORT_DESC:
             # 倒排：交期最晚的订单先占资源（自交期向前的派工近似）
             orders.sort(key=lambda o: (o["dueDate"], o["priority"]), reverse=True)
         elif mode == SORT_BOTTLENECK:
@@ -477,6 +481,38 @@ class PoolEngine:
             "makespan": makespan, "onTimeCount": on_time,
         }
 
+    @staticmethod
+    def _dispatch_key(rule: str, order: dict[str, Any], routings: list[dict], ops_by_code: dict[str, dict]) -> tuple:
+        """Return stable dispatch keys for the optimize rule catalog."""
+        steps = [step for step in routings if step.get("productCode") == order.get("productCode")]
+        duration = sum(float(step.get("stdTimePerUnit") or 1) for step in steps) * float(order.get("quantity") or 1)
+        due = str(order.get("dueDate") or "9999-12-31")
+        release = str(order.get("releaseDate") or order.get("releaseAt") or "0000-01-01")
+        priority = -int(order.get("priority") or 0)
+        def _day_number(value: str, fallback: float) -> float:
+            try:
+                return datetime.fromisoformat(value[:10]).toordinal()
+            except (TypeError, ValueError):
+                return fallback
+        due_day = _day_number(due, 3652059.0)
+        release_day = _day_number(release, 1.0)
+        slack = max(0.0, (due_day - release_day) * 24 * 60 - duration)
+        if rule == "SPT":
+            return (duration, due, priority, str(order.get("orderNo") or ""))
+        if rule == "LPT":
+            return (-duration, due, priority, str(order.get("orderNo") or ""))
+        if rule == "PRIORITY":
+            return (priority, due, release, str(order.get("orderNo") or ""))
+        if rule == "FIFO":
+            return (release, due, priority, str(order.get("orderNo") or ""))
+        if rule == "CR":
+            return ((due_day - release_day) / max(duration, 1e-9), priority, str(order.get("orderNo") or ""))
+        if rule == "ATC":
+            score = (abs(priority) or 1) / max(duration, 1e-9)
+            score *= pow(2.718281828, -slack / max(4 * duration, 1.0))
+            return (-score, due, priority, str(order.get("orderNo") or ""))
+        return (due, priority, release, str(order.get("orderNo") or ""))
+
     # ---------------- 占槽：设备级 + 可选班组并发（SC-11） ----------------
     def _place(self, cursor: datetime, duration_min: float, eq_id: int,
                eq_busy: dict[int, list[tuple[datetime, datetime]]], world: World,

server/gateway/app.py

@@ -220,6 +220,7 @@ class FlexScheduleRequest(BaseModel):
     orderIds: list[int] = Field(default_factory=list)
     window: str | None = None                          # short/mid/long/full（SC-12）
     enforceTeams: bool | None = None                   # SC-11 班组约束
+    engine: str | None = None                           # CLOSED_LOOP / OPTIMIZE
 
 
 class TimeUpdateRequest(BaseModel):
@@ -2440,6 +2441,7 @@ def create_app() -> FastAPI:
                 actor=req.sessionId or "web",
                 window=req.window,
                 enforce_teams=req.enforceTeams,
+                engine_type=req.engine,
             )
         except (ValueError, PermissionError) as exc:
             return {"error": str(exc)}

shared/schemas/schedule_result.schema.json

@@ -8,7 +8,7 @@
   "properties": {
     "versionId": { "description": "排产版本 ID", "type": "integer" },
     "versionNo": { "description": "版本号（如 V20260716-003）", "type": "string" },
-    "engineType": { "description": "引擎类型", "type": "string", "enum": ["RULE", "CP", "GA", "HYBRID", "EXTERNAL"] },
+    "engineType": { "description": "引擎类型", "type": "string", "enum": ["RULE", "CP", "GA", "HYBRID", "EXTERNAL", "OPTIMIZE"] },
     "strategy": { "description": "策略模板", "type": "string" },
     "status": { "description": "版本状态", "type": "string", "enum": ["DRAFT", "PUBLISHED", "ARCHIVED"] },
     "orderCount": { "description": "参与排产的订单项数", "type": "integer" },

tests/golden/test_optimize_engine.py

@@ -0,0 +1,75 @@
+from __future__ import annotations
+
+from server.aps_domain.closed_loop_runtime import run_closed_loop_candidate
+from server.engines import get_engine
+from server.engines.optimize_engine import normalize_dispatch_rule
+from server.engines.pool_engine import PoolEngine
+
+from tests.golden.test_closed_loop_runtime import BUSINESS_DATE, _ready_world
+
+
+def _next_id_factory():
+    counters: dict[str, int] = {}
+
+    def next_id(kind: str) -> int:
+        counters[kind] = counters.get(kind, 0) + 1
+        return counters[kind]
+
+    return next_id
+
+
+def test_optimize_factory_and_rule_catalog_are_available():
+    assert get_engine("OPTIMIZE").name == "OPTIMIZE"
+    assert normalize_dispatch_rule("DELIVERY_FIRST") == "EDD"
+    assert normalize_dispatch_rule("first-in-first-out") == "FIFO"
+    assert normalize_dispatch_rule("unknown") == "EDD"
+
+
+def test_dispatch_rules_have_stable_ordering_keys():
+    routings = [
+        {"productCode": "SHORT", "stdTimePerUnit": 2},
+        {"productCode": "LONG", "stdTimePerUnit": 10},
+    ]
+    ops = {}
+    short = {"productCode": "SHORT", "quantity": 1, "dueDate": "2026-08-05", "priority": 2, "orderNo": "SO-S"}
+    long = {"productCode": "LONG", "quantity": 1, "dueDate": "2026-08-04", "priority": 1, "orderNo": "SO-L"}
+    assert sorted((long, short), key=lambda row: PoolEngine._dispatch_key("SPT", row, routings, ops)) == [short, long]
+    assert sorted((short, long), key=lambda row: PoolEngine._dispatch_key("LPT", row, routings, ops)) == [long, short]
+
+
+def test_optimize_runs_through_closed_loop_v2_and_records_provenance():
+    world = _ready_world()
+    result = run_closed_loop_candidate(
+        world,
+        _next_id_factory(),
+        business_date=BUSINESS_DATE,
+        engine_type="OPTIMIZE",
+        sort_mode="SPT",
+    )
+
+    assert result["solveStatus"] == "FEASIBLE"
+    assert result["engineType"] == "OPTIMIZE"
+    version = world["flexScheduleVersions"][-1]
+    assert version["engineType"] == "OPTIMIZE"
+    assert version["solverId"] == "optimize-dispatch"
+    assert version["algorithmId"] == "optimize.spt"
+    assert version["schedulingSolutionV2"]["assumptions"][0]["code"] == "OPTIMIZE_ENGINE_V1_ADAPTER"
+    assert version["schedulingSolutionV2"]["provenance"]["solverId"] == "optimize-dispatch"
+
+
+def test_optimize_blocker_keeps_engine_identity_and_zero_artifacts():
+    world = _ready_world()
+    world["materials"][1]["stock"] = 0
+    world["routings"] = []
+    result = run_closed_loop_candidate(
+        world,
+        _next_id_factory(),
+        business_date=BUSINESS_DATE,
+        engine_type="OPTIMIZE",
+    )
+
+    assert result["solveStatus"] == "BLOCKED"
+    assert result["engineType"] == "OPTIMIZE"
+    assert result["woCount"] == 0
+    assert world["flexScheduleVersions"][-1]["engineType"] == "OPTIMIZE"
+    assert world["flexWorkOrders"] == []