44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
"""Tiny ADMM-lite solver for AidMesh.
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This is a toy, deterministic solver to illustrate cross-organization coordination.
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"""
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from __future__ import annotations
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from typing import Dict
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import time
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from .core import LocalProblem, SharedSignals, DualVariables, PlanDelta
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def admm_step(
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contract_id: str,
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local_problem: LocalProblem,
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shared: SharedSignals,
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dual: DualVariables,
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rho: float = 1.0,
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) -> PlanDelta:
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"""Perform a single, toy ADMM step and return a PlanDelta.
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The toy logic simply pushes a delta that moves assets towards the forecasted needs
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weighted by current multipliers. This is not production-grade optimization.
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"""
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# Simple heuristic: adjust each asset towards forecast needs, bounded by available capacity
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delta: Dict[str, float] = {}
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for asset, need in shared.forecast.items():
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current = local_problem.assets.get(asset, 0.0)
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cap = shared.capacity_proxies.get(asset, 0.0)
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# target: min(need, cap) but respect current
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target = max(0.0, min(need - current, cap))
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# apply a small portion dictated by rho and a multiplier if available
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mult = dual.multipliers.get(asset, 1.0) if isinstance(dual, DualVariables) else 1.0
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delta[asset] = target * (0.5 * rho) * mult
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# Build a PlanDelta with a simplistic signature and timestamp
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pd = PlanDelta(
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delta=delta,
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timestamp=time.time(),
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author="admm-lite-solver",
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contract_id=contract_id,
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signature="toy-signature",
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)
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return pd
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