Benchmark & Case study
Algorithm for Routing Optimisation
Challenge
Problems
- Slow and manual routing process
- No visibility of the impact of the different variables
Root causes
- Available tools are heavy and perform poorly
- Solutions dependent on one resource and his knowledge
- Little flexibility to improve solutions through adding/removing stops and drivers
- Difficulty performing sensitivity analysis to study the impact of each restriction
Solutions
- Creation of a mathematical model and algorithm to define the initial solution
- Development of a genetic algorithm (based on meta heuristics) to optimise routes
- Solutions displayed in a visual format to ease understanding
- Set-up of a user-friendly interface to guarantee successful deployment of the tool
Results
Process Lead Time
Process Lead Time decreased by 90%.
Costs : FTE + km
Costs reduced by 10%.
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