Analyze Mission Outcomes and Allocate Response Units

Problem Statement

You are tasked with evaluating the operational performance of emergency response units across fleet dispatch missions. Management wants to understand unit reliability and determine the optimal unit to prioritize for critical missions.

Write a function evaluate_and_allocate_units(missions, units, min_missions) that processes historical mission data and returns a structured operational summary.

Requirements

1. Eligible Win Rates:

   • Calculate the success rate (successful missions / total missions) for each unit that has participated in at least min_missions missions.
   • Round the rate to 3 decimal places.

2. Rest Period Analysis:

   • Classify each mission as either "well_rested" (rest_days >= 3) or "fatigued" (rest_days < 3).
   • Compute the aggregate success rate for each group across all missions. Round to 3 decimal places. If a group has zero missions, its rate should be None.

3. Unit Allocation Recommendation:

   • Identify the single best eligible unit (top_unit_id) to deploy.
   • Rank units by:
     1. Highest win rate (descending).
     2. Lowest average damage_cost across all their missions (ascending).
     3. Smallest unit_id (ascending) in case of a tie.
   • If no units meet the min_missions threshold, top_unit_id should be None.

Function Signature

def evaluate_and_allocate_units(
    missions: list[dict],
    units: list[dict],
    min_missions: int
) -> dict:
    pass

Input Format

• missions: List of dictionaries, each containing:
  • "mission_id" (int)
  • "unit_id" (int)
  • "success" (bool)
  • "damage_cost" (float)
  • "rest_days" (int)
• units: List of dictionaries containing "unit_id" (int) and "unit_name" (str).
• min_missions: Integer threshold for evaluation eligibility.

Output Format

Return a dictionary with the following shape:

{
    "win_rates": {unit_id: win_rate, ...},  # Only for units with >= min_missions
    "rest_comparison": {
        "well_rested_rate": float or None,
        "fatigued_rate": float or None
    },
    "top_unit_id": int or None
}

Example

missions = [
    {"mission_id": 1, "unit_id": 101, "success": True, "damage_cost": 500.0, "rest_days": 4},
    {"mission_id": 2, "unit_id": 101, "success": False, "damage_cost": 1200.0, "rest_days": 1},
    {"mission_id": 3, "unit_id": 102, "success": True, "damage_cost": 200.0, "rest_days": 3},
    {"mission_id": 4, "unit_id": 102, "success": True, "damage_cost": 400.0, "rest_days": 2},
]
units = [
    {"unit_id": 101, "unit_name": "Alpha"},
    {"unit_id": 102, "unit_name": "Bravo"}
]
min_missions = 2

# Output:
# {
#     "win_rates": {101: 0.5, 102: 1.0},
#     "rest_comparison": {
#         "well_rested_rate": 1.0,  # missions 1 and 3: 2/2 = 1.0
#         "fatigued_rate": 0.5      # missions 2 and 4: 1/2 = 0.5
#     },
#     "top_unit_id": 102
# }