Logistics Route Optimization

Challenge‍

A delivery company was experiencing inefficient routing that significantly increased fuel consumption and delivery times. Their manual route planning couldn't effectively account for traffic patterns, delivery windows, vehicle capacities, and last-minute changes. This resulted in excessive fuel costs, missed delivery windows, and underutilized vehicle capacity.

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Solution

‍An AI route optimization system with real-time adjustments using Akkio and Make.com that:

• Analyzed historical traffic patterns and delivery time data
• Incorporated real-time traffic information and weather conditions
• Optimized delivery sequences considering time windows, package priorities, and vehicle capacity
• Dynamically adjusted routes as conditions changed throughout the day
• Balanced workload across available drivers
• Provided turn-by-turn navigation with expected time windows to drivers

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Implementation‍

The implementation was completed over 5 weeks:

1. Data integration from GPS, delivery management, and traffic information systems
2. Historical pattern analysis to establish baseline optimization parameters
3. Algorithm development for initial route optimization
4. Real-time adjustment system implementation
5. Driver mobile app development and training

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Results

• 18% reduction in fuel consumption through more efficient routing
• 26% more deliveries completed per vehicle per day
• 1.5 FTE equivalent driver capacity gained without additional hiring
• On-time delivery rate improved from 82% to 96%

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Environmental Impact

The fuel reduction represented approximately 120 tons of CO2 emissions avoided annually, supporting the company's sustainability goals.

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