AgentSkillsCN

Optimize Shipping Route

优化运输路线

SKILL.md

Skill: Optimize Shipping Route

Domain

transportation

Description

Calculates optimal shipping routes considering distance, transit time, cost, and carbon emissions across multimodal transportation options.

Tags

transportation, logistics, route-optimization, supply-chain, multimodal

Use Cases

  • •Freight route planning
  • •Mode selection optimization
  • •Transit time estimation
  • •Carbon footprint calculation

Proprietary Business Rules

Rule 1: Mode Selection Criteria

Optimal mode selection based on shipment characteristics, urgency, and cost targets.

Rule 2: Hub Network Optimization

Routing through hub network with proprietary transit time and cost matrices.

Rule 3: Carbon Calculation

Emissions calculation using carrier-specific emission factors.

Rule 4: Service Level Matching

Route options filtered by service level requirements.

Input Parameters

  • •shipment_id (string): Shipment identifier
  • •origin (dict): Origin location details
  • •destination (dict): Destination location details
  • •cargo_specs (dict): Weight, volume, type
  • •service_level (string): Express, standard, economy
  • •delivery_deadline (string): Required delivery date
  • •preferences (dict): Cost vs speed vs sustainability weights

Output

  • •recommended_route (dict): Primary route recommendation
  • •alternative_routes (list): Alternative options
  • •transit_time_days (float): Estimated transit time
  • •total_cost (float): Estimated shipping cost
  • •carbon_footprint_kg (float): CO2 emissions estimate

Implementation

The routing logic is implemented in route_optimizer.py and references transit data from transit_matrix.csv.

Usage Example

python
from route_optimizer import optimize_route

result = optimize_route(
    shipment_id="SHIP-2024-001",
    origin={"city": "Shanghai", "country": "CN", "port": "CNSHA"},
    destination={"city": "Chicago", "country": "US", "port": "USCHI"},
    cargo_specs={"weight_kg": 5000, "volume_cbm": 25, "type": "general"},
    service_level="standard",
    delivery_deadline="2026-02-15",
    preferences={"cost": 0.5, "speed": 0.3, "sustainability": 0.2}
)

print(f"Route: {result['recommended_route']}")

Test Execution

python
from route_optimizer import optimize_route

result = optimize_route(
    shipment_id=input_data.get('shipment_id'),
    origin=input_data.get('origin', {}),
    destination=input_data.get('destination', {}),
    cargo_specs=input_data.get('cargo_specs', {}),
    service_level=input_data.get('service_level', 'standard'),
    delivery_deadline=input_data.get('delivery_deadline'),
    preferences=input_data.get('preferences', {})
)