cwicr-crew-optimizer

# CWICR Crew Optimizer ## Business Case ### Problem Statement Crew planning challenges: - Right mix of workers? - Optimal crew size? - Balance cost vs productivity? - Match skills to work? ### Solution Optimize crew composition using CWICR labor productivity data to balance cost, output, and skill requirements. ### Business Value - **Optimal productivity** - Right-sized crews - **Cost efficiency** - No overstaffing - **Skill matching** - Proper worker mix - **Schedule support** - Meet deadlines ## Technical Implementation ```python import pandas as pd import numpy as np from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from enum import Enum from datetime import date, timedelta class WorkerType(Enum): """Types of workers.""" FOREMAN = "foreman" JOURNEYMAN = "journeyman" APPRENTICE = "apprentice" LABORER = "laborer" OPERATOR = "operator" HELPER = "helper" class Trade(Enum): """Construction trades.""" CONCRETE = "concrete" CARPENTRY = "carpentry" MASONRY = "masonry" STEEL = "steel" ELECTRICAL = "electrical" PLUMBING = "plumbing" HVAC = "hvac" PAINTING = "painting" ROOFING = "roofing" GENERAL = "general" @dataclass class Worker: """Worker definition.""" worker_type: WorkerType trade: Trade hourly_rate: float productivity_factor: float = 1.0 overtime_multiplier: float = 1.5 @dataclass class CrewComposition: """Crew composition...